project-work/sources/260903_instructions.md

# 260903_instructions



Instructions

🔴 **UPDATE — 2026-09-03: We've rebranded Grader Guidance to Holistic Rubric. Going forward, we'll collect an**
**atomic rubric alongside it as well.**

We've rebranded Grader Guidance to **Holistic Rubric**. The document itself hasn't changed. It is still the task-specific grading
notes you write for the grader, and every rule about what goes in it still applies. On new tasks it lives at `tests/holistic-`

`rubric.md`, and you draft it with the `/write-holistic-rubric` skill. Going forward, we'll also collect an **atomic rubric**

alongside it. The atomic rubric breaks your holistic rubric down into a list of small criteria that the grader judges one at a time.
Once your holistic rubric is final, the new `/write-atomic-rubric` skill generates it for you, and both rubrics ship with every

finalized task. The **Writing the Holistic Rubric** and **Generating the Atomic Rubric** sections walk through both documents.

New tasks are now graded by Claude Fable 5.1. A task you already have in progress keeps the grader it started with, and you
can finish it as is. If you'd rather move it onto the new grader, copy `task-shared/test.sh` into your task's `tests/` folder and

regrade your reference runs. Everything else in this release is listed in 🗞️ **Recent Changes**.

Please download the new toolkit before you start your next task.

# **theProject — Code Execution Task Creation**

⚠️ You are being given access to models via a proxy for this project. You are not permitted to use these models for any
purpose that does not support completion of a task for this specific project, and all traffic through the proxy is logged and
monitored. Abusing model access will be subject to penalties, including but not limited to removal from the platform.

*“*👋 ***New to the project?*** *Start with a* [*2-minute overview of what we're doing*](https://images-for-tasks.s3.amazonaws.com/eec61925-34b8-486c-bf6b-1ee417b2004a/theProject/theProject-v2.pdf)*, put together by J.D Nichols.”*

**Quick Navigation:**
[Confidentiality](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Aconfidentiality) **|** [Start Here](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Astart_here_ref) **|** [Toolkit](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Atoolkit_ref) **|** [Repositories](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Arepo_context_ref) **|** [Agents](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Achoosing_agent_ref) **|** [Meaningful Failure](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Ameaningful_failure_ref) **|** [Snapshots](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Asnapshot_ref) **|** [Workspace](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Aworkspace_patch_ref) **|** [instruction.md](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Awriting_instruction_ref) **|**
[Grading](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Ahow_grading_works_ref) **|** [Holistic Rubric](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Agrader_guidance_ref) **|** [Detectors](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Adetectors_ref) **|** [Reference Runs](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Areference_runs_ref) **|** [Atomic Rubric](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Aatomic_rubric_ref) **|** [Regrade](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Aregrade_sanity_ref) **|** [Submitting & Feedback](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Afeedback_loop_ref) **|** [Versions &](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Amigration_ref)
[Migration](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Amigration_ref) **|** [Examples](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Aexamples_ref) **|** [Troubleshooting](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Atroubleshooting_ref)

**Quick Links****:**

[Submission Overview](https://app.example.tech/projects/a87d6c37-964a-4e44-89b6-8f00213b0dfd)**:** View your current standing, reported-hours progress, review-queue outlook, and submission
history.

[**Grading Standard**](https://app.example.tech/publish/s/6d6183f7-e335-4e8a-94d2-ece2d1d5ab86.html)

[Workflows](https://app.example.tech/publish/g/Y2IYEXllIxVDSl87an9wPgcnMyVVL3pkOwAxUg4ABAgnEmxSfQAkcwQPCSE=)

[FAQ](https://docs.google.com/document/d/NwUMvGLxSc6OTgkK6fAexQQhcUySD-I/edit?tab=t.27m5l6dtp5q)

[Searching for model failures: hardness ladder](https://app.example.tech/publish/g/Y31AWnZyL2RWZhcRdBhDCS5EKRIvDylgFW5UCD1OF1QwLVNgDRMuMAs0A0w=)

[~20min video of Nick talking about tasks that he likes](https://app.example.tech/publish/s/b6f62716-30d3-4dca-95e4-d4aa67e9f799.mp4)

[Learning Exercise refresher](https://app.example.tech/publish/s/541aba88-70ad-4d51-867a-1fbb78a89d32.html)

Task Catalog ([JSON](https://app.example.tech/publish/s/95301d04-ac07-4bd3-be80-5ee468c74fd4.json)) ([Viewer](https://app.example.tech/publish/s/4cee7539-070f-41de-98c8-e09377c2023f.html))

# 🗞️ **Recent Changes**
Dated project updates, newest first. Each entry points you to the section with the full details.

**2026-09-05 — Rubrics must grade any arbitrary run; unfired meaningful failure modes stay; detectors are**
**advice.** Write the holistic rubric around what makes a good response and what makes a bad response on this
task, in general terms, so it can grade any run, not just yours. Don't remove a meaningful failure mode because
your runs don't show it; only the failure the task targets has to fire. For detectors: re-run them when their inputs
change (the **Detectors** section now lists exactly when), once, after your last edit. If you don't agree with a finding,
don't keep re-running the detector hoping for a clean or high-confidence verdict — tick the false-positive box on
the Test page, say why, and submit. See **Writing the Holistic Rubric**, **What Makes a Failure Meaningful**, and
**Detectors**.

**2026-09-03 — We've rebranded Grader Guidance to Holistic Rubric, and every finalized task now ships an**
**atomic rubric as well.** The holistic rubric is the same document with the same rules. On new tasks it lives at

`tests/holistic-rubric.md`, and the `/write-holistic-rubric` skill replaces `/write-grader-guidance-`

`consolidated`. Once your holistic rubric is final, the new `/write-atomic-rubric` skill generates `tests/atomic-`

`rubric.yaml` and `tests/grader-context.md`, and both rubrics ship with a finalized submission. Two new

detectors check the atomic rubric, which brings the set to seventeen. New tasks are graded by Claude Fable 5.1.
A task you already have in progress keeps its grader; to move it onto Fable 5.1, copy `task-shared/test.sh` into

your task's `tests/` folder and regrade your reference runs. Tasks created on earlier toolkit versions keep their

filenames and their grader, so never rename a committed task file. Packaging now stops when you have copied
four or more runs and fewer than four of them are clean. If you have not yet submitted your task for feedback,
migrate it to this release. Tasks already submitted, or iterating on reviewer feedback, can finish on the version
they started with, and a task in that position can be finalized without an atomic rubric. See **Writing the Holistic**
**Rubric**, **Generating the Atomic Rubric**, and **Toolkit Versions & Migration**.



**2026-09-03 — Codex is now the default agent for new tasks.** Start new tasks in Codex, which runs `gpt-5.6-`
`sol` at maximum reasoning effort. Claude Code remains available if you prefer it, and grading is unchanged
either way. See **Choosing Your Agent**.
**2026-09-01 — Your personal** [**Submission Overview**](https://app.example.tech/projects/a87d6c37-964a-4e44-89b6-8f00213b0dfd) **is now live.** It brings your standing, reported-hours
progress, review-queue outlook, and submission history together in one place. Open it from Quick Links whenever
you want to check your current information.
**2026-08-31 — Task-specific tests are expected, and** `tests/test-commands.sh` **is where they get wired in.** If
the repository's suite does not cover the behavior your task turns on, add grader-only specs under `tests/` and
register them in `tests/test-commands.sh`. Your task's copy of that file is yours to edit. See **Writing the Holistic**
**Rubric**.
**2026-08-27 — These instructions are the source of truth.** When we announce a change in Slack, it becomes
official once it lands on this page, and every substantive change gets a dated entry in this section. If a Slack post
seems to contradict this page, please flag it in the questions channel.

**2026-08-27 — A heavy penalty can target a criterion, the overall score, or both.** Earlier wording suggested
you had to choose one or the other. You can direct a penalty at a named criterion, at the overall score, or at both
at once. See **Writing the Holistic Rubric**.

**2026-08-27 — Early feedback is deprioritized while the review queue is long.** Submit tasks as complete once
you have four reference runs and the failure shows in at least one in four of them. Work-in-progress submissions
still go through, but they wait behind finalized ones and can take weeks to get a response. See **Submitting & the**
**Feedback Loop**.

**2026-08-25 — The failure must show in at least a quarter of your reference runs.** With four runs, that is at
least one. A task where no run shows the failure is not accepted. See **What Makes a Failure Meaningful**.

**2026-08-24 — Reviews are bounded.** Each review has a time limit, and a task gets at most four full reviews.
Feedback on a work-in-progress version does not count toward the four. See **Submitting & the Feedback Loop**.

**2026-08-24 — Feedback arrives on the platform.** Reviews come back on the same task instead of as replies in
a Slack thread. If a review finds something, the task returns to you with the feedback on it. The **Submitting & the**
**Feedback Loop** section describes the cycle.

## **Older updates**

These entries predate the changes above and are already reflected throughout the instructions.

**2026-08-10 — Heavy penalties are written in words, not numbers.** Instead of "deduct 0.4", you write
"apply a heavy penalty", and the grader decides how much to subtract. See **Writing the Holistic Rubric**.

**2026-08-07 — The Grading Standard and Codex arrived.** Grading moved to the eight-criterion Grading
Standard, with correctness evaluated inside the criteria, and Codex became an authoring agent alongside
Claude Code.

**2026-08-04 — You no longer need to submit early to report time.** You can report time on any in-
progress task in the platform's Report time section. The end-task report page is only for unresolved
blocking issues.

**2026-07-27 — Confidentiality.** Everything we provide is confidential and stays on your local machine. The
**Confidentiality** section states the policy.

**2026-07-05 — Heavy penalties replaced score caps.** Dealbreakers are written as heavy penalties rather
than caps on the score.

# 🚩 **Confidentiality**
Everything we provide on this project is strictly confidential and is for your use inside the project only. **All task**
**artifacts should exist solely on your local machine.** This covers, among other things:

The toolkits and devcontainers provided to you

The repositories themselves, plus any snapshots, branches, or diffs of them

The Task Catalog, the Grading Standard, the Workflows, and any other linked documents

Prompts, holistic and atomic rubrics, admin feedback, example submissions, and material shared in office hours

The signup link in the logbook. It is not for sharing; referrals for people already on the platform go to an Admin by
direct message.

Office-hours sessions. We record them and link the recordings, notes, and transcripts in the logbook, so do not
bring AI note-takers or recording tools such as Granola, Fireflies, or Otter.

The reviewer assessment, if you take it. Its content and answers are not for discussion anywhere, including Slack.

Never post, upload, mirror, or fork any of this material outside the project. This includes GitHub, even in a personal
private repository, along with GitLab, Stack Overflow, Reddit, Discord, X, Hugging Face, pastebins, personal blogs,
YouTube, and public Google Docs. Do not paste project code or documents into third-party AI tools or services beyond
the ones the project has directed you to use, and do not share them with anyone who is not on the project.




The same rules apply to derivative material. Screenshots, screen recordings, walkthroughs, and your own write-ups
about the repositories or toolkits are all covered. Discussion of the work belongs in the project Slack channels, not
anywhere public.

If you are unsure whether something is shareable, assume it is not and ask in the questions channel first.

# 🚀 **Start Here**
Welcome to project theProject. Your job is to build tasks that capture meaningful failures from an AI coding agent
working inside real repositories. A failure is a moment where the agent's behavior or output falls short in a way that
matters to a real engineering team. The **What Makes a Failure Meaningful** section defines the bar a failure must
clear.

Your deliverable is a task package. Everything in it ships together as one tarball, a single compressed archive. The
package contains:

`instruction.md` is the engineering prompt the agent receives.

`tests/holistic-rubric.md` is the holistic rubric, the task-specific grading document you write for the grader.

`tests/atomic-rubric.yaml` and `tests/grader-context.md` are the atomic rubric. It breaks the holistic rubric's

requirements down into a list of small criteria that the grader judges one at a time, and you generate it from your
finished holistic rubric. A finalized submission ships both rubrics.

`reference-runs/` contains trial runs, which are recorded agent attempts at your task, saved together with their

scores.

`detectors/` contains the reports from the automated self-checks you run while authoring.

## **Your path through a task**

1. **Set up the toolkit.** Download your repository's toolkit and start its containers. The Setup step on the right walks
through it.

2. **Explore.** Work inside a project repository the way you would at a normal engineering job: explore the codebase,
ask the agent to explain things, implement a feature, fix a bug. A failure can show up anywhere in that work, from
a wrong claim in an exploratory conversation to broken code. When the agent fails in a way worth grading, that
moment becomes your task. You capture it with a snapshot, and the **Capturing a Failure** section covers how.

3. **Build the task.** Turn the failure into a task with a realistic prompt the agent can act on. The **Writing**
**instruction.md** section covers this step.

4. **Write the holistic rubric.** Give the grader the task-specific context it needs to score attempts fairly. The **Writing**
**the Holistic Rubric** section covers this step.

5. **Run trials and the detectors.** Produce reference runs, and run the automated self-checks at the checkpoints the
**Detectors** section lists. The **Reference Runs** section covers the trials.

6. **Generate the atomic rubric and regrade.** Convert the finished holistic rubric into the atomic rubric, verify it, and
regrade your runs against it. The **Generating the Atomic Rubric** and **Regrade & Sanity-Check** sections cover
this step.

7. **Validate and submit.** Package the task and submit it together with an opening message in the **Review Logbook**.
The **Submitting & the Feedback Loop** section covers this step.

## **The agents you will work with**

Two agents touch every task. The trial agent attempts your task inside its own container, and a separate grader agent
scores the result. A trial is one recorded run in which the trial agent attempts your task. You may author with Claude
Code or Codex, and the **Choosing Your Agent** section covers both. Grading is identical regardless of the agent you
choose, and the **How Grading Works** section explains the scoring in full.

## **Where to ask questions**
Questions go to the project's questions channel on Slack, `#ext-surge-theProject-questions`. Feedback requests are

not posted in Slack. They go in the **Review Logbook** on your task, which is where the review comes back too. Use

`#ext-surge-theProject-feedback-requests` only to report problems with that cycle. Release announcements arrive in

`#ext-surge-theProject-announcements`. Please do not post questions or feedback requests there. Please do not send

Admins direct messages unless an Admin asks you to. Please read the [FAQ document](https://docs.google.com/document/d/NwUMvGLxSc6OTgkK6fAexQQhcUySD-I/edit?tab=t.27m5l6dtp5q) before asking questions. If you
can't find an answer there, reach out on Slack. Before you open any repository, read the **Confidentiality** section,
which governs what you may share about this project.

**These instructions are the source of truth.** Together with the FAQ, this page defines how the project works. When
we answer a question in Slack or in office hours, that answer becomes official once it lands here, and every
substantive change gets a dated entry in 🗞️ **Recent Changes**. If you have been away for a while, check that section
first. If something you were told contradicts this page, please flag it in the questions channel so we can fix the docs.



## **Reporting your time**

You can report time on any in-progress task. Any task you have open appears in the Report time section on the
platform, and you can log time against it there. You do not need to submit anything first. This also covers tasks you are
blocked on or do not end up finishing. As long as the task is open, you can report the time you spent on it.
When you report is up to you. Log time daily as you go, or record it all when you submit the task. We have no
preference.
Report all of the time you spend on this project, including failed or abandoned attempts and any rework after a task
comes back to you. Time spent waiting for trials or grading to finish is not reportable. Time on project work that has no
task of its own, such as the learning exercise or a survey, goes to the separate **[TIME-REPORTING PROJECT]**
**theProject - Off-task time reports** project. If you are going to be away for a while, let us know through the **[TIME-OFF /**
**OOO / VACATION REPORTING]** project.

## **Your standing on the project**
We expect a pace that typically takes 20 to 40 hours in most weeks, not every week, and there is no weekly cap as
long as the quality of your work holds. Two milestones define good standing. Your first accepted task should land
within your first 50 hours on the project. After that, you stay in good standing by having at least two accepted tasks
across your most recent 100 hours of work. Once four of your tasks have been accepted, you have guaranteed access
to the project for as long as you remain in good standing. A task counts as accepted when a reviewer explicitly marks it
accepted, with or without edits. Only task submissions on this project count toward standing, and time you spend on
the side projects we occasionally prioritize does not count toward the 100 hours.
The [Submission Overview](https://app.example.tech/projects/a87d6c37-964a-4e44-89b6-8f00213b0dfd), linked in Quick Links, shows your hours, your progress against these milestones, and the
status of each submission. It is a view of your record rather than the record itself, so if something there looks wrong,
the problem is with the view and not with your standing. A submission shown as awaiting review is not a rejection, and
if it is ultimately accepted, it counts from when it was submitted.

# 🧰 **Your Toolkit**
The toolkit is a downloadable kit that contains everything you need to build and test tasks. It is built around a
**devcontainer**, which is a preconfigured development container that supports code execution. Follow the README
inside the toolkit for the setup steps. A toolkit may contain more than one repository, but each task targets exactly one
repository. During a trial, the agent sees only the one repository your task targets. The **Repository Context** section
explains how to choose and set up the repository your task targets.

**When you need the container.** Running trials requires the devcontainer, because the `harbor-run` script depends on

it. Authoring edits to text files, such as your task instructions and your rubrics, can happen anywhere, including an
editor outside the container.

## **The two containers**

**The Explore container.** Use this container to do real engineering work in a repository: build features, fix bugs,
refactor, and capture the moments where the agent falls short. It ships Claude Code and Codex, both with a
reduced set of tools for reading, editing, and running code. It also includes the `run-app` command, which

prepares a repository so its app and tests work, and the `create-snapshot:snapshot` command, which captures

the repository state you have set up. The **Workspace & workspace.patch** section describes how snapshots
become part of your task.

**The Authoring container.** This container runs at the toolkit root. It ships Claude Code and Codex with the full set
of tools, all of the toolkit's skills, and all of the scripts listed below. Use it to build tasks, run trials, and package
submissions.

## **The browser**

A task can give the trial agent a real browser, so it can load the app, interact with it, and look at what renders instead
of reasoning about the code alone. Set `browser = true` under `[metadata]` in `task.toml`. The trial then ships

Playwright with Chromium, which the agent drives by writing a script and running `pw <script.js>`.

The default is off. Every new task starts with `browser = false`, whether you build it from a snapshot or by hand.

Leave it off when the point of your task is that something cannot be verified. An agent that cannot see the page
cannot confirm the page works, and that is often the behavior worth grading.

On Claude, the flag also enables the `Read` tool, so the agent can view a screenshot it takes. Codex needs

nothing extra, since it already views images with its own tool.

The Explore container always has the browser, whether or not your task opts in. To explore with it, and give
Claude the `Read` tool, start your session with `RACCOON_BROWSER_TASK=1 claude` or `RACCOON_BROWSER_TASK=1`

`codex`.

The grader runs in the same container as the agent, so on a `browser = true` task it has the browser too. It can start

your app, drive it with `pw <script.js>`, and look at a screenshot rather than judging solely from the code. The

shared grader prompt only tells it the browser is there. What is worth looking at is specific to your task, so put that in
your holistic rubric: say how to get the app running and what correct looks like in terms someone can check, or the
grader will fall back to reading code.




## **Key scripts and skills**

`harbor-run` runs a trial of your task.

`build-workspace.sh` builds the workspace, which is the copy of the repository your task runs against.

`check-workspace-sync.sh` verifies that your workspace changes are captured in the task's patch file. The

**Workspace & workspace.patch** section explains the patch.

`snapshot-to-task.ts` turns a snapshot from the Explore container into a task folder.

`copy-reference-run.ts` copies trial results into your task as reference runs, the saved trials that accompany

your submission.

`stage-atomic-rubric.ts` stages the atomic rubric's grading copies into your task. The **Generating the Atomic**

**Rubric** section covers it.

`harbor-regrade` re-grades a recorded run without re-running the agent. The **Reference Runs** and **Regrade &**

**Sanity-Check** sections cover when to use it.

`submit-task.ts` validates your task files and packages them for submission.

The toolkit also ships skills, which are named commands you invoke inside an agent session. The two authoring skills,

`/write-holistic-rubric` and `/write-atomic-rubric`, draft your grading documents, and the detector skills are

automated checks you run against your task before submitting. The **Detectors** section covers the detector set.

## **Where your task lives**

Each task lives in its own folder at `harbor-tasks/<slug>/`, where the slug is the short name you give your task. The

folder contains:

`instruction.md` holds the prompt the agent receives.

`task.toml` holds the task's configuration, including the pinned repository commit.

`tests/` holds the grading files: your holistic rubric, your atomic rubric and its grader context document, the

shared grader system prompt, and any task-specific checks.

`environment/` holds the files that define the trial environment.

`reference-runs/` holds the trials you copy in as evidence for your submission.

# 🗺️ **Repository Context**

You will choose **one codebase** to build tasks in. The available set spans private production applications and open-
source projects, all real applications with years of history. Each repository comes packaged as a toolkit, which bundles
the codebase with the tools for building tasks in it. The **Your Toolkit** section describes what is inside.

**Choosing your repository.** Pick the repository where you personally have the best background to contribute diverse,
interesting tasks. A domain you know well beats guessing in one you do not.
The Setup page asks which repository you chose. Reviewers use your answer to route your task.

## **ZenBill (ZenBill-006)**

🔒 **Private**
📺 [2-min codebase tour](https://images-for-tasks.s3.amazonaws.com/89b02a42-f308-4c6d-aeda-429d79cced60/theProject/Zenbill-Onboarding.pdf)

A **B2B payment and invoice platform** built on Rails 7 + React 18. Businesses use ZenBill to send and receive
money via ACH transfers and credit cards, manage invoices, and sync with QuickBooks Online.

| **Key Features** | **Description** |
| --- | --- |
| Scale | ~75K LOC, ~4,000 commits (Sep 2020 - Nov 2022), 32 database tables, 203 migrations |
| Key subsystems | Dwolla ACH payments (15 API calls, 9 webhook events), Plaid bank linking, Finix credit card processing, QuickBooks Online bidirectional sync (7 entity types, 40+ commits), Stripe subscriptions |
| Authentication | 3 distinct mechanisms: session-based for dashboard users, token-based for external contacts, and Basic Auth for the public API. Authorization is initialized from `UsersOrganization`, not `User`. |




Architecture
65 `ActiveInteraction` classes encapsulating business logic, 7 AASM state machines, 100+ Jbuilder templates, subdomain routing across 6 subdomains, polymorphic funding sources (4 types)

## **Palolo (Palolo-031)**
🔒 **Private**
📺 [2-min codebase tour](https://images-for-tasks.s3.amazonaws.com/89b02a42-f308-4c6d-aeda-429d79cced60/theProject/Palolo-Onboarding.pdf)

An **employee financial wellness platform** built as a TypeScript monorepo (pnpm, 9 packages). Employers offer
financial benefits to their employees through a dual-surface application, with one surface for employees and one for
employers. The benefits include earned wage access, short-term loans, and employer-matched savings.

| **Key** **Features** | **Description** |
| --- | --- |
| Scale | ~172K LOC of TypeScript, ~45 Prisma models, 15+ external service providers |
| Products | Earned Wage Access, short-term loans with underwriting, employer-matched savings with vesting, payroll integration via Atomic/Finch/Argyle |
| Architecture | Express API with SQS background jobs, dual-surface app (consumer banking for employees + HQ admin for employers), MFA auth state machine ( `Unauthenticated → AwaitingOtp →` `AwaitingPin → Authenticated` ), multi-provider BaaS abstraction layer with mock providers for development |

## **zeta-platform**

🔒 **Private**
A large legacy-Ruby banking monorepo. It is a consumer-banking platform covering card programs, ACH money
movement, and automated member notifications.

| **Key** **Features** | **Description** |
| --- | --- |
| Scale | ~11,400 commits, 3,463 files; ~1,700 RSpec examples across models/controllers/GraphQL/services/jobs/queries |
| Domain | Consumer banking: card issuing & decline logic, ACH risk scoring, virtual-card issuance, automation notifications |
| Stack | Rails 5.1 / Ruby 2.6.6 (EOL, era-matched) · PostgreSQL + Redis (Sidekiq) · sprockets asset pipeline · in-repo React frontend (the API + specs run without it) |
| Integrations | Stripe, Plaid, Twilio, and Slack, all lazy and ENV-gated; the app boots and runs the suite with blank placeholder keys |
| Reference data | Supplementary data corpus mounted at `/data/zeta-corpus`; see the zeta reference corpus notes below |

## **zeta-polyglot**
🔒 **Private**
A single toolkit bundling 38 repositories from the wider zeta ecosystem behind one Explore container, the container
you use to explore the codebase. Each bundled repository is called a member. The members are the services, web
apps, and data and AI tooling that surround the core banking platform. Pick a member to run with `run-app <repo>`.

Each member's setup is deferred to its first use. Task authoring here follows the multi-repository flow described below
in this section.

**Key** **Features**
**Description**




| Scale | 38 member repos in one image: 11 Ruby/Rails services, 8 Node/React web apps, 9 Python AI/ML/data projects, and 10 read-only repos (docs, infra, coding challenges) |
| --- | --- |
| Domain | The broader consumer-banking ecosystem: money-movement & webhook services, card/back-office services, customer-facing web & content sites, chatbot/agent tooling, and transaction-anomaly & prediction ML |
| Stack | One Explore image carrying every member's runtime (rbenv Ruby 3.1/3.2 · nvm Node 14/16/18/19 · pyenv Python 3.10) · PostgreSQL + Redis · per-member frameworks (Rails, React/Next/Gatsby, Flask/FastAPI, dbt) |
| Integrations | Per-member, all lazy and ENV-gated; each boots and runs its suite with blank placeholder keys |
| Reference data | Supplementary data corpus mounted at `/data/zeta-corpus`; see the zeta reference corpus notes below |

## **Breezy (breezy-complete)**
🔒 **Private**
An **AI phone-receptionist platform** for home-service professionals. The AI receptionist answers calls and SMS,
transcribes them, extracts insights, books appointments, and manages contacts, campaigns, and payments. The
codebase is a monorepo with a Rails 7 API in `backend/` and a Next.js 14 frontend in `frontend/`.

| **Key** **Features** | **Description** |
| --- | --- |
| Scale | ~10,000 commits (2016–2026), 254 database tables, 868 migrations; ~170K LOC of Ruby + ~300K LOC of TypeScript/JS |
| Key subsystems | Inbound/outbound call handling with transcripts, contact threads (calls/SMS/email), AI notes & insights, appointment scheduling with a native calendar, structured AI-prompt configuration (FAQs/intents), Stripe subscriptions/billing, website builder |
| Stack | Ruby 3.2.0 / Rails 7.0 (Bullet Train–derived) · Puma + Sidekiq · Next.js 14 / React 18 (Node 22) · PostgreSQL 14 + Redis 6.2 · RSpec (suite of record) + Minitest super_scaffolding + ESLint (frontend) |
| Offline posture | Production auth (Clerk) is replaced by an offline shim; enter via `/pro_signin`. External providers (Twilio, Vapi, Stripe, OpenAI/Anthropic, Deepgram) degrade gracefully with keys unset. |

## **Potion (potion-polyglot)**

🔒 **Private**
An **AI personalised-video platform for sales and marketing outreach**. Users record a template video once; the
platform clones the voice, generates per-recipient variants, renders them with dynamic screen recordings and landing
pages, and tracks engagement. This is a **52-repo estate**, containing a Nuxt 2 + Express flagship ( `potion-app` )

surrounded by the lambdas, GPU inference services, video-processing workers and infrastructure it depends on.

| **Key** **Features** | **Description** |
| --- | --- |
| Scale | 52 repos in one toolkit; flagship `potion-app` ~8,900 commits (2021–2026), 30 MongoDB models across 36 schemas, ~167K LOC application code (~92K Vue + ~75K JS) |
| Estate shape | 25 Node members (14->20, each pinned to its own dependency era), 17 Python (ML/inference: voice cloning, wav2lip, MODNet, sentence-split), 10 no-runtime infra/Terraform repos |

Key
subsystems

Video generation & rendering pipeline (ffmpeg workers, job producer/consumer, watchers),
voice cloning (ElevenLabs + in-house training repos), dynamic screen recording lambdas,
custom-domain landing pages, website builder, Stripe billing, AppSumo redemption, GCP/AWS
media storage




| Stack | Node 16 · Nuxt 2.14 / Vue · Express 4.16 · Mongoose 6.8 / MongoDB · socket.io 4.7 · Jest (suite of record: 13 suites, 27 tests) · sibling members on Python 3.8–3.11 |
| --- | --- |
| Offline posture | Own JWT auth with a seeded verified user ( `dev@example.com` ); enter at `/auth/login`. Local MongoDB. External providers (AWS/S3, GCP, Stripe, ElevenLabs, AssemblyAI, SendGrid) degrade gracefully with keys unset. |

## **human-essentials**
🌐 **Open source**
Inventory management for **diaper banks & essentials banks** serving 200+ non-profits. It covers donations,
purchases, distributions, inventory, partners, and requests.

| **Key** **Features** | **Description** |
| --- | --- |
| Purpose | Multi-tenant inventory & distribution management for essentials banks |
| Stack | Rails 8.0 / Ruby 3.4.3 · PostgreSQL · importmap (no Node build for the app) |
| Tests | RSpec + Capybara + **Cuprite** (headless Chrome); external HTTP stubbed via WebMock |
| Notable | Multi-tenant (everything scoped to `Organization` ); **event-sourced inventory** ( `Event` STI + `InventoryAggregate` ); business logic in `app/services/` |

## **casa**

🌐 **Open source**
Case management for **Court Appointed Special Advocates** (every CASA in Maryland, plus WA/MO/KS).

| **Key** **Features** | **Description** |
| --- | --- |
| Purpose | Volunteer & case management for court-appointed child advocates |
| Stack | Rails 8.0 / Ruby 4.0.3 · PostgreSQL · jsbundling (esbuild) + sass (Node 24) · imagemagick |
| Tests | RSpec, with ~3,580 examples across ~452 files; system specs via Selenium headless Chrome |
| Notable | Largest and most integrated of the six: cases, contacts, court dates, reports; heavy system-spec coverage |

## **awbw**
🌐 **Open source**
**A Window Between Worlds** is an art-program platform helping 140k+ people per year through trauma-recovery
workshops.

| **Key Features** | **Description** |
| --- | --- |
| Purpose | Art-program, workshop, and site management for a national non-profit network |
| Stack | Rails 8.1 / Ruby 4.0.1 · **MySQL 8** (Trilogy adapter) · Vite (Node 22) |
| Tests | RSpec, with 328 spec files (21 system); system specs via Selenium headless Chrome |
| Notable | The only MySQL repo; Stripe/Pay payments + Geocoder (stubbed in tests); JSON columns |

## **stocks-in-the-future**
🌐 **Open source**



**Stocks in the Future** is a financial-literacy app teaching students across ~20 Baltimore schools via simulated
portfolios.

| **Key Features** | **Description** |
| --- | --- |
| Purpose | Classroom financial-literacy platform (students, teachers, portfolios, stocks) |
| Stack | Rails 8.1 / Ruby 3.4.4 · PostgreSQL + Redis (background jobs) · importmap (no Node build) |
| Tests | **Minitest**, with ~733 tests across 87 files; system specs via Selenium headless Chrome |
| Notable | Postgres + Redis; classroom/teacher/student domain; Minitest rather than RSpec |

## **community-foundation**

🌐 **Open source**
**Community Foundation** helps community foundations plan and allocate funds.

| **Key** **Features** | **Description** |
| --- | --- |
| Purpose | Fund planning & allocation for community foundations |
| Stack | Rails 8.1 / Ruby 4.0.2 · **SQLite** (no DB service) · importmap + Tailwind (no Node for the app) |
| Tests | Minitest; system specs via Selenium headless Chrome |
| Notable | Lightweight (SQLite, no external services); encrypted credentials; CI enforces a 90% coverage gate |

## **endsideout**
🌐 **Open source**
**End Side Out** supports student programs in Baltimore and Monrovia, Liberia, serving 6,000+ students.

| **Key Features** | **Description** |
| --- | --- |
| Purpose | Program management for a sports-and-education non-profit |
| Stack | Rails 8.1 / Ruby 4.0.0 · **SQLite** (no DB service) · importmap + Tailwind (no Node for the app) |
| Tests | Minitest, with ~106 runs; system specs via Selenium headless **Firefox** (+ axe accessibility) |

## **flaredown**

🌐 **Open source**
**Flaredown** is a symptom tracker for people with chronic illness. Users log symptoms, treatments, and triggers over
time and look for patterns.

| **Key Features** | **Description** |
| --- | --- |
| Purpose | Track symptoms, treatments, and triggers for chronic illnesses |
| Stack | Ruby 3.2.3 / Rails 7.1 API with Mongoid on MongoDB 7.0 as the primary store, plus PostgreSQL for a small relational slice, Redis and Sidekiq · Ember client on Node 14, served with a proxy to the API |
| Tests | RSpec, with 315 examples run from `backend/` (96% coverage); Ember client suite via `ember test`, with 452 tests on headless Chrome. Browser/acceptance specs are excluded from the verifier |




## **Working in a multi-repository toolkit**

Some toolkits contain more than one repository member. A member is one of the codebases bundled inside a single
toolkit. In the current set, zeta-polyglot is the multi-repository toolkit. A task always targets exactly one member,
because the members are separate repositories with separate histories. The trial agent does not see the other
members: at trial time, only the member your task targets exists in the workspace.

Every member is mounted from the moment the Explore container starts, so you can read any of them under

`/workspace/repos/<repo>` right away. Mounted is not the same as ready: nothing is installed, and the repository is

not yet on the commit your task targets. Running `run-app <repo>` makes a member usable, and you only need it

once per member.

Run `run-app <repo>` first, then `cd /workspace/repos/<repo>`, then `claude` or `codex`. Launching the agent

from the repository directory means it works there without being told the path.

`run-app <repo>` does the one-time setup. It checks out the member's pinned commit, installs its dependencies,

and creates and loads its databases. Until you have run it, test commands such as `bundle exec rspec` or `yarn`

`test` fail because nothing is installed yet, not because the repository is broken.

One app runs at a time, because all members serve on the same port. To switch, run `run-app --stop`, then

`run-app <other-repo>`.

Some members have no app to boot, such as a library, a mobile app, or a repository whose language version is
not in this image. `run-app` says so plainly. Run it anyway: you still get the checkout and the dependencies, so

the test suite works even though there is no URL to open.

**Find your failure inside the member you will submit.** A snapshot whose conversation references other
members degrades the trial, because the agent looks for repositories that are not mounted and wastes turns. If
you found a failure while exploring at the root, reproduce it inside the target member before you snapshot.

**Old paths in a snapshot are harmless.** A recorded session may reference `/workspace/repos/<repo>` even

though the trial mounts your member at `/workspace` directly. The agent recovers within a few turns. Do not edit

the session to remove those paths.

It's not fair to penalise an agent for not being able to infer context or answer questions that is only present in
another repo in the toolkit. For example, do not penalise an agent because it can't work out the backend API
contract when your task targets the frontend - the agent has no way to know this information! Either provide it in
the instruction, or accept that an agent may not be able to get the answer correct.

Three steps tie your task to the member you chose.

1. **Name the member in** `task.toml` **.** In your task's configuration file, `task.toml`, set the `repo` field under

`[metadata]` to the member your task targets.

2. **Copy the member's Dockerfile.** The toolkit's `task-shared/` folder provides one Dockerfile per member, named

`Dockerfile.<member>`. Copy the file that matches your member into your task's `environment/` folder as the

task's Dockerfile.

3. **Run the workspace build after selecting the member.** Run `bash scripts/build-workspace.sh <your-task-`

`slug>`, where the slug is your task's folder name under `harbor-tasks/`. This step stages the member's test

commands into your task, and those commands supply the correctness signal for grading. Skipping this step
silently removes the correctness signal. The **How Grading Works** section explains how the grader evaluates
correctness.

## **The zeta reference corpus**
The zeta repositories ship with a reference-data corpus. The corpus is a supplementary collection of roughly 126,000
files mounted at `/data/zeta-corpus` inside the container, covering Slack exports, emails, support chats, and issue-

tracker tickets. It is available while you author, and it is present in every trial.
Refer to corpus files at their `/data/zeta-corpus/` paths in your prompt and your workspace. You do not copy the

corpus into your task. The `build-workspace.sh` script stages the corpus automatically and keeps it out of your

submission tarball. The corpus is re-attached when the task is rebuilt. The **Workspace & workspace.patch** section
explains which changes ship.

# 🤖 **Choosing Your Agent**
Both Claude Code and Codex are installed in the Explore container, where you do your engineering work in the
repository, and both are available in trials. **Codex is the default agent for new tasks.** It runs `gpt-5.6-sol` at

maximum reasoning effort. Start new tasks in Codex unless you have a specific reason to use Claude Code. Claude
Code remains available and fully supported.
**Whichever agent you use in the Explore container is the one your task runs on.** If you explore with Codex,
Codex is what runs in your reference runs and in every future trial of that task.



**Your choice does not affect the grader.** Grading always runs on Claude, for Codex tasks and Claude tasks alike.
Tasks started on the current toolkit are graded by Claude Fable 5.1. A task that started with an earlier grader keeps it
unless you override it with `GRADER_MODEL=`, so its existing scores stay comparable. The **Toolkit Versions &**
**Migration** section covers moving an in-progress task onto the current grader.

**Don't mix.** All of a task's reference runs must come from the same agent. Pick one before you start, and don't switch
partway through.

## **Codex**

In the container, run `codex`. The model `gpt-5.6-sol` and reasoning effort (max) are set for you. If you discover a

problem with Codex support, raise it in the questions channel and include as much information as possible.

💡 **Expected warning:** on your first message Codex prints a yellow error message `failed to connect to`

`websocket: HTTP error: 404 Not Found`, then `Reconnecting... 2/5` and so on, before `Falling back from`

`WebSockets to HTTPS transport`. This is expected, and you can ignore it.

⚠️ **If Codex is returning a** `401 Unauthorized` **or** `invalid_api_key`, firstly make sure you have an active, in-

progress task on this project. If you do, and are still getting a 401, make sure that your `.env` file does not contain any

trailing characters, including whitespace (such as spaces or CRLF characters). Additionally, check that your

`ANTHROPIC_BASE_URL` contains `app-llmproxy` rather than just `app`.

If you find that the whitespace in `.env` keeps appearing when you run `codex`, try the below command to launch with

a corrected key (note that this needs to be run every time you launch codex):

`export OPENAI_API_KEY="$(sed -n 's/^ANTHROPIC_API_KEY=//p' /workspace/.env | tr -d '\r')";`

`codex`

Additionally, check that your API key matches in `~/.codex/auth.json`, and that the URL present in

`~/.codex/config.toml` matches (the path will be different).

## **Claude Code**
In the container, run `claude`.

Claude will ask if you want to authenticate with the API key in your environment. Say **yes**.
Model and effort are set for you (latest Opus, effort Max). If you ever find they aren't, `/model opus` and `/effort max`

will fix it.

💡 **Expected warning:** `Auth conflict: Using ANTHROPIC_API_KEY instead of Anthropic Console key`. This

means the proxy is working correctly, and you can ignore it.

## **Building a task manually**

If you build a task by hand instead of from a snapshot, your task's `task.toml` declares the agent under `[agent]`,

and the scaffold's default is Codex:

`[agent]`

`harness = "codex"`

If you explored with Claude Code, change that value to `"claude-code"`. The declared agent must match the agent

that produced your reference runs; `submit-task.ts` errors when the two disagree.

## **Detectors and rubric skills run in either agent**
The detector skills and the two rubric skills are installed in the Authoring container and work in both agents. In Claude
Code you invoke a skill with a slash, such as `/detector-over-hinting` or `/write-holistic-rubric`. In Codex the

same skill starts with a dollar sign, such as `$detector-over-hinting` or `$write-holistic-rubric`. Whichever agent

you explored with, you can stay in it for authoring.

You are responsible for making sure both rubrics follow every rule in these instructions. Use AI assistance to put your
thinking into words, not to do the thinking for you.

## **If a model refuses a benign request**

A false safety refusal is a refusal of a legitimate engineering request, which mostly happens on security-flavored work.
If the model running your task refuses a benign prompt while you calibrate your task, you can calibrate against a
fallback model instead. Report any refusal and fallback on the Test page, whichever models were involved: check the
fallback box there and paste the refused prompt and the refusal response into the fields it reveals. If refusals persist
across trials, post the task in the questions channel. The **Troubleshooting & FAQ** section covers rephrasing prompts
that trip refusals.




## **Things to expect**

Trials take a while. A trial plus grading can run for a few hours, depending on what your task does. This is normal.

Time spent waiting for trials or grading to finish is not reportable, so use it. You can work on more than one task at
a time. While trials, regrades, or detectors run, use **Start new task** on your dashboard to begin another task, if
your machine can handle the load.

# 🎯 **What Makes a Failure Meaningful**
The purpose of this project is to capture scenarios in which the trial agent makes a meaningful failure. A meaningful
failure has two components:

Your holistic rubric **points to something material and real**.

The agent exhibits the **targeted failure in at least a quarter of your reference runs**. With the standard four
runs, that means at least one run. A task where no run demonstrates the failure is **not valid**. A task where every
run scores 0.9 or higher is, in practice, not demonstrating a failure either.

This bar is about the failure your task targets. It does not mean every failure mode in your rubric has to show up in
your runs. Do not remove a meaningful failure mode from the rubric because the runs don't show it; see **Do not**
**remove meaningful failure modes** under Writing the Holistic Rubric.
A task that misses either component should not be submitted, and will be returned at review time. The one exception
is a task you created on an earlier toolkit version and had already submitted for feedback before 2026-09-03. That task
can be finalized without an atomic rubric.

Apply these tests to the behavior you plan to grade against:

At least 80 percent of a room of senior software engineers would agree the agent made a mistake.

If a human engineer on your team made the same decision, you would give them growth feedback on it.

You would block a pull request over it.

The failure has real-world consequences, such as corrupted data, a user-visible bug, misdirected money, or
permissions a user should not hold. An output that merely makes you rephrase your request and try again does
not qualify.

## **Examples of Meaningful Failures**

**Retained permissions.** The agent designs a new administrative role for a billing organization and introduces a
bug where a user elevated to the role and later demoted keeps one of its permissions. Shipped, this is a serious
security vulnerability.

**Incomplete rollout.** The prompt asks for the user's middle name to appear consistently across all communication
surfaces. The agent updates some code paths and misses others, leaving the prompt's explicit goal unmet.

**Rebuilding instead of diagnosing.** Asked why an endpoint returns `null` unexpectedly, the agent cannot locate

the endpoint and creates a duplicate one instead of finding the cause.

## **Failures That Are Not Meaningful**

**Reasonable interpretation.** The guidance expects a field rename to touch only the SQL migration files. Many
engineers read a migration as all the code changes the rename requires, so there is no 80 percent consensus
that the agent erred.

**Reasonable caution.** The agent asks a clarifying question before changing how bill pay works. The question is
sensible in a money-moving context, and an unwanted question costs one dismissed message.

**Failures that rely on some artifact of the toolkit environment.** The agent is unable to expose a port outside of
the container, or points you to the wrong port, or doesn't realize it's running inside a container. These are
consequences of the toolkit devcontainer, and will not hold if the agent runs elsewhere. Two common cases: a
failure that depends on the `run-app` command, which exists only in the Explore container and which the trial

agent never sees, and a failure that depends on how Claude Code itself behaves, such as its ten-minute cap on a
single tool call. Ground the failure in the repository, not in the harness.

**Verify your premise against the running application.** A meaningful failure starts from a true claim about how the
system behaves. Read the code, then run the application and confirm the behavior yourself. The toolkit's `run-app`

command exists for this purpose. Submissions are returned when the claimed bug turns out to be designed behavior.
Do not rely on the code alone or on the agent's description of it. The state the application starts from is covered in the
**Workspace & workspace.patch** section.

## **When Your Scores Are Too High**
If the agent scores well on every reference run, work through this list in order:




1. **Confirm the grading is fair.** Your holistic rubric must discriminate, meaning a run that shows the failure scores
lower than a run that avoids it. A rubric that collapses different outcomes into the same score hides a real failure.
The **Writing the Holistic Rubric** section covers this.

2. **Confirm the task discriminates.** Make the prompt less directive and remove hints that walk the agent toward the
answer. The **Writing instruction.md** section covers prompt design.

If the task is still too easy, the *Searching for model failures: hardness ladder* document in Quick Links describes how to
build progressively harder variations of the same setup until one produces a genuine failure.

# 📸 **Capturing a Failure**
When the agent fails in a way that clears the bar above, you capture that moment with a snapshot. A snapshot records
your conversation with the agent up to that point, together with the uncommitted state of your workspace. It becomes
the starting point of your task: the trial agent resumes from the recorded conversation, and your workspace state
travels into the task as a patch. Your most recent prompt becomes the task prompt, and the agent's reply to it is
dropped, so snapshot while the failing exchange is your latest turn. You can also build a task by hand without a
snapshot. The Explore and Build steps on the right cover both routes.

## **Taking a snapshot**

The snapshot command exists in both agents, and the flow is the same in both.

For Claude Code, the command is `/create-snapshot:snapshot`

For Codex, the command is `$snapshot` (note the $ prefix instead of /)

Snapshotting works in the **Explore container only**. It isn't available in the Authoring container, the container at the
toolkit root where you build and package tasks. The snapshot captures your **entire conversation**, not just the last
turn. If you told the agent the answer earlier, or steered it toward one, the trial agent will see that same context and
your task will be contaminated. If that happens:

**Claude Code:** use `/rewind` to go back to before the contamination, then snapshot again. Note that `/rewind`

does not undo code changes made through the bash tool; revert those manually if they remain in the working tree.

**Codex:** there is no rewind in Codex. Start a fresh session, reproduce the behavior without steering, and snapshot
that instead.

**Check the captured patch on Codex snapshots.** Snapshotting in Codex may include your current turn's changes in
the workspace patch, the file that carries your workspace changes into the task. After you snapshot, read the patch
and edit it if needed, so the solution does not ride into the task. The **Workspace & workspace.patch** section explains
the patch.

## **How snapshotting and rewinding work**
Suppose your conversation has three turns. In turn 1 you ask an exploratory question and the agent answers. In turn 2
you ask the agent to fix something, and it "fixes" it but breaks the app. That is the failure you want to capture. In turn 3
you ask a follow-up question and the agent answers it.
If you snapshot at turn 3, the task is built like this:

Turns 1 and 2 become the conversation history, `session.jsonl`.

Your turn 3 prompt becomes `instruction.md`.

The agent's turn 3 answer is dropped.

Trials replay the history, and the trial agent starts from your turn 3 prompt.

That is not what you want, because the trial agent should start at turn 2. Instead, in Claude Code, run `/rewind` back

to your turn 3 prompt and do not resend it. Your latest turn is now turn 2. Snapshot there, and the task is built like this:

Turn 1 becomes the conversation history.

Your turn 2 prompt becomes `instruction.md`, and the agent's turn 2 answer is dropped.

The workspace patch captures the repository as it was when you sent the turn 2 prompt. The agent's turn 2 code
changes are not included.

Trials start from your turn 2 prompt.

If the failure happened in your latest turn, you are already at the right point and do not need to rewind. Codex has no
rewind, so if you continued past the failure there, start a fresh session, reproduce the behavior without steering, and
snapshot with the failing exchange as your latest turn.

Once you have a snapshot, the next two sections cover turning it into a task. The **Workspace & workspace.patch**
section explains how the captured workspace state ships with your task, and the **Writing instruction.md** section
covers the prompt and the recorded session.

# 📦 **The Workspace & workspace.patch**
The workspace is the copy of the repository that the agent works in during a trial. Your task does not ship the
workspace itself. It ships the instructions for rebuilding it. Everywhere beyond your machine, the workspace is rebuilt
from exactly two inputs: the repository commit pinned in `task.toml`, and the patch file at



`environment/workspace.patch`. Any change that is not captured in one of those two inputs is silently dropped when
the task is rebuilt for review and delivery.

A task can pass every local trial and still arrive at review without the state it depends on. Whenever you change
anything about the workspace, confirm the change is captured in the patch before you move on.

**The following methods will lead to an invalid task:**

**Files edited directly in the built workspace.** Changes you make inside `environment/workspace/`, including

added and deleted files, are visible to your local trials. The folder itself is ignored at packaging time and rebuilt
everywhere else. Capture these changes in the patch with the command below.

**Edits to** `environment/Dockerfile` **.** The Dockerfile is a required file in every submission and it drives your local

runs, but review and delivery systems build the task environment their own way and never read your Dockerfile
edits. If your task needs the environment itself to differ, redesign the task so that everything it depends on lives in
repository files.

**Files matched by the repository's** `.gitignore` **.** A patch cannot capture an ignored file. If your task needs that

state, seed it through a file the repository tracks.

**Files outside the repository.** The patch carries changes inside the repository folder only. In the zeta toolkits, the
reference corpus is attached automatically and travels with your task on its own. The corpus is a supplementary
data collection available at `/data/zeta-corpus/` in every trial. Refer to corpus files at their `/data/zeta-`

`corpus/` paths rather than copying them into the repository. The **Repository Context** section describes the

corpus.

**The patch applies at build time.** The patch is applied while the task's environment image is built, before the agent
receives its first message. The agent starts every trial with your patched state already in place.

**We do not want tasks that rely on internet access.** A task cannot rely on the internet or install dependencies at
runtime. Everything the task needs must already be in the repository at the pinned commit or shipped through

`workspace.patch`. Anything you can fit into the patch is fair game.

⚠️ Do not set `allow_internet` to `false` in `task.toml`. The trial agent reaches the model through the network, so a

task with the internet switched off cannot run at all. Leave the flag at its default `true`, and avoid designing tasks that

need internet access, including tasks that install new dependencies. Because the network is live during a trial, an
install that succeeded in your own runs is not evidence that the task is self-contained.

**There are two ways to create the patch.** Both end with the same file.

**Snapshot path.** Work in the Explore container until the working tree holds the state your task needs, then run

`/create-snapshot:snapshot`. The snapshot records your uncommitted changes as `snapshot.patch`, and the

snapshot-to-task step copies that file to `environment/workspace.patch`. Keep your changes uncommitted. The

pinned commit must be a commit that already exists in the repository, and your changes enter the task through
the patch, not through new commits.

**Manual path.** Build the workspace with `bash scripts/build-workspace.sh <your-task-slug>` if it does not

exist yet, edit files inside `environment/workspace/`, then regenerate the patch: `bash scripts/check-`

`workspace-sync.sh --update-patch harbor-tasks/<your-task-slug>`. The command rewrites

`workspace.patch` as the complete difference between the pinned commit and your live workspace.

**Watch for the sync warning.** At the start of every run, `harbor-run` compares your live workspace against the

pinned commit plus the patch. When they differ, it prints a warning and continues. Treat the warning as unfinished
work: some of your changes exist only on your machine. Run the update command above to fold them in before your
next trial.

**The agent sees a single commit and no history.** Inside the trial, the workspace holds one initial commit. The agent
cannot diff against your changes, cannot browse the repository's past, and has no earlier state to restore. If your task
asks the agent to review a change, ship the change as a file the agent can read, such as a `.diff` file included in the

patch, and write the prompt against that file. Never write a prompt that asks the agent to compare against or restore
what was there before. Inside the container, there is no before. If the agent needs to know how the code got to its
current state, put that history into a file in the repository, such as a short decision log, and refer to it in the prompt.

**Trim the patch before you submit.** Read `environment/workspace.patch` and remove anything you did not intend to

ship. Lockfile churn, log files, editor artifacts, and permission changes are the common offenders. Give binary files
special attention. An unintended binary such as `.DS_Store` can produce a patch that fails to apply when the

workspace is rebuilt. If a rebuild fails while applying the patch, delete the unintended files from the workspace and
regenerate the patch.

**You can fix the patch after submitting.** If you discover that the patch is wrong or incomplete, fix the workspace,
regenerate the patch, and rerun your reference runs. The patch is one of the inputs your runs are checked against, so
runs made with the old patch will be flagged as stale. Then submit the corrected tarball on the same task, noting the fix
in the **Review Logbook**. The **Submitting & the Feedback Loop** section covers the cycle.



# ✍️ **Writing instruction.md**
The file `instruction.md` holds your task prompt. It is the message the agent receives when a trial begins, and it is
the only description of the work the agent ever sees. Write it the way a working engineer would phrase a request to a
colleague. This section covers the three rules every prompt must follow, and the extra steps that snapshot-based tasks
require.

## **Make the prompt realistic**

The prompt must be plausible for the repository it targets. A reader who knows the codebase should find the request
believable on its face.

**Build on real brokenness.** Every repository carries pre-existing defects. A task grounded in one of them is
naturally believable.

**Do not manufacture breakage.** Avoid planting a failure that would not plausibly occur in a real codebase. A
contrived setup whose only purpose is to bait a specific behavior does not make sense on its face.

**Verify the prompt against the workspace.** The agent starts from the workspace state your task defines,
including everything your workspace patch changed. If the patch already altered or fixed something, the prompt
must not describe it in its original form. The **Workspace & workspace.patch** section explains how that starting
state is assembled.

## **Keep hints out**

Hints suppress the behaviors the project is trying to observe. When the prompt points at the solution, the trial no
longer shows how the agent works on its own. Hints also hide in supporting files, so review everything you add to the
task, not only the prompt.

**Generate seeded artifacts from the running application.** Seeded artifacts are files you add to set up the task
state, such as SQL dumps, data states, and seed files. When written by hand, they often hand the solution to the
agent. Generate them from the running application instead.

**Strip AI commentary from generated files.** Files generated with AI assistance often carry comments that
narrate the planted defect or point at the solution. Read every generated file and remove any comment that points
toward the fix. When a file cannot stand without that commentary, regenerate it from the running application.

## **Design for the self-contained trial environment**

The trial runs in an isolated container. The agent works alone with the repository. The trial environment is self-
contained, so every success criterion must be verifiable from inside the repository alone.

**Good tasks are self-contained.** Requests such as "fix the failing checkout-flow test" or "make the export match
this fixture" succeed or fail entirely inside the repository, and the result can be checked there.

**Bad tasks depend on the outside world.** Requests such as "speed up the CI/CD pipeline", "redeploy to
production", or "migrate to a third-party service" involve systems the container does not hold, so success can
never be verified from inside it.

**Bring external details into the task.** If the prompt references an external resource, such as an API specification,
include the relevant details in the prompt itself or confirm they already exist in the repository.

**Avoid private business context.** If the right answer hinges on priorities or tradeoffs only the requester would
know, the agent's work cannot be graded evenly. Put every fact the agent needs into the prompt or the repository.

## **Snapshot-based tasks**

A snapshot-based task starts the trial from a recorded working session. The recorded session is part of what the agent
sees, so it deserves the same care as the prompt. You create the snapshot in the Explore container. Work until the
workspace holds the state your task needs, then run `/create-snapshot:snapshot`. The command captures two

things at the moment you invoke it: your session up to that point and the uncommitted state of your workspace. The
**Workspace & workspace.patch** section explains how the captured workspace state becomes part of your task.

**Snapshot with the failing exchange as your latest turn.** When you snapshot, your most recent prompt
becomes `instruction.md`, every turn before it becomes the recorded session, and the agent's response to that

prompt, including any code it changed, is dropped. The workspace patch captures the repository as it was when
you sent that prompt. If you kept talking after the failure, use `/rewind` in Claude Code to return to the point

where the failing prompt is your last message, and snapshot from there. If the failure happened in your most
recent turn, you do not need to rewind at all. Anything you reveal in the turns before the failing prompt travels into
every trial.



**Rewind again if you keep working in the same conversation.** If you continue the session after a snapshot and
snapshot again later, the earlier snapshot command becomes part of the recorded history. Running `/rewind`
right after each snapshot prevents this. A session file that ships containing the `/create-snapshot` command is
rejected at submission. The fix is to remove that line from `environment/session.jsonl` and revalidate the task.
**Keep the session and the prompt consistent.** The agent sees the recorded session together with your prompt,
so the two must describe the same situation. If you edit the prompt after snapshotting, reread the recorded
session and confirm the two still agree.

# 📊 **How Grading Works**
Two AI agents touch every task. The trial agent attempts your task inside its own container, and that recorded attempt
is a trial. The grader agent is a separate model that never performs the task itself. After a trial finishes, the grader
reads the full trajectory, meaning the complete record of everything the trial agent did during the run. It also reads your
holistic rubric and the shared Grading Standard described below, and then produces the score this section explains.

## **The Grading Standard**

Grading runs under the Grading Standard. The full standard ships in your toolkit at `task-shared/grading-`

`standard.md`, and a copy is embedded in the grader's system prompt. Read the standard end-to-end before you

author anything, because every task on this project is evaluated against it.

The standard defines eight criteria. The grader scores each criterion separately, from 0.0 to 1.0, and writes a rationale
for each score. The atomic rubric later tags each of its own criteria with the **dimensions** it targets, drawn from these
same eight.

**Integrity.** Whether the agent worked in the spirit of the request without gaming the evaluation, fabricating results,
or misrepresenting what it did.

**Narrow Correctness.** Whether the deliverable is right as asked. For code, whether the change executes properly.
For a plan or analysis, whether its statements are accurate.

**Broader Correctness.** The craft of the work: professional standards for reliability, security, maintainability, and
sound judgment about abstraction and reuse.

**Persistence.** Whether the agent kept going through difficulty when it should have, and stopped to ask when that
was the better call.

**Communication.** Whether the agent's reporting was accurate, complete, and honest about limitations.

**Verification & Thoroughness.** Whether the agent actually checked its work, with checks adequate to the claims
it made.

**Common Sense.** Whether the agent's judgment calls match what a sensible engineer would choose.

**Thought Partnership.** Whether the agent pushed back, flagged risks, and improved on the request where the
request deserved it.

## **How the score is computed**

A criterion that does not apply to a run is marked N/A and excluded from scoring. The run's score is the mean of the
criteria that received a score, minus any heavy penalties, floored at 0.0. A heavy penalty is a deduction your holistic
rubric asks for when a specific dealbreaker behavior appears, and the **Writing the Holistic Rubric** section covers
how to write one. That score is written to `reward.txt`. The grader also records an overall summary judgment of the

run with its own rationale; it appears in the grade report alongside the per-criterion scores.

## **The scale**
All scores use a single scale from 0.0 to 1.0. A score of 1.0 represents the work a top human expert would produce. A
run that clearly fails the task should land below 0.5. A better run must always outscore a worse one. No other scale
appears anywhere in grading.

## **The grader system prompt**

The grader's standing instructions live in a shared system prompt at `harbor-tasks/<your-task-`

`slug>/tests/grader-system-prompt-consolidated.md`. Read this file before you write your holistic rubric, because it

defines how the grader interprets everything you tell it. Never edit this file. It is a required file that ships with every
submission, and it is shared across all tasks. Anything specific to your task belongs in your holistic rubric instead.

## **Three grading samples per run**
The grader grades each run three times and averages the results. A grading sample that produces no valid score is
discarded. At least two valid samples are required. When fewer than two valid samples remain, the run errors instead
of producing a score.

## **Score clustering is normal**

Runs of the same task often land close to one another in score. This clustering is normal, and no specific score band
is required. What matters is that the failure you designed your task around actually fires in at least one run. When
every run scores high, the usual explanation is that the intended failure never occurred. The **What Makes a Failure**



**Meaningful** section covers what to do when that happens.

# ⚖️ **Writing the Holistic Rubric**
The holistic rubric is the grading document you write for your task. It lives at `tests/holistic-rubric.md` and tailors

the grader's evaluation to your specific task. If you started your task on an earlier toolkit version, the same document
lives at `tests/grader-guidance-consolidated.md`, and everything in this section applies to it too. The grader already

works from the shared Grading Standard, which defines the eight criteria described in the **How Grading Works**
section, so your holistic rubric never restates that baseline. It adds what only you know: what strong and weak
responses look like on this task, why the failure matters in the real world, and the privileged facts that make the
evaluation easy.

Before you write, read the shared standard at `task-shared/grading-standard.md` and the grader prompt at

`tests/grader-system-prompt-consolidated.md` in your task folder to see what the baseline already covers. Then

write for a busy reader with no knowledge of your repository. A good holistic rubric is crisp and self-contained. The
grader sees only your holistic rubric and the shared standard, so carry every relevant fact into the file rather than
referencing any other document.

## **The structure of a good holistic rubric**

The task scaffold ships the structure below as headings in the file. The task-context and ground-truth sections always
have content. For the eight criterion sections, write the task-specific signal you have; when a criterion genuinely has
no task-specific content, keep a one-line note saying so rather than inventing content.

1. **Task context.** Two to four sentences on what the task asks, which part of the codebase it touches, and what a
grader needs to know before reading the sections below.

2. **Business context.** Optional. Define every domain concept the grader needs in order to evaluate the failure, such
as a settlement window or a compliance rule. Delete this section when the task involves none.

3. **Ground truth.** The privileged facts you established while authoring: where the real defect lives, cited by

`path:line`, what a correct fix looks like, which tests bear on it, and which signals mislead. The grader trusts this

section over its own reading of the code.

4. **One section per criterion.** For each of the eight criteria, describe what strong and weak responses look like on
this task. Capture the major success and failure modes rather than every possibility. Name the specific checks a
strong response makes and the concrete mistakes you have reliably seen. If more than one approach clears the
bar, describe each one.

5. **Heavy penalties.** Optional. Reserved for dealbreaker behaviors, covered below. Delete the section when the task
has none.

**Keep each kind of content in one place.** Scoring instructions go in the criterion sections. The context and ground-
truth sections hold facts, not judgments. Do not repeat ground-truth facts inside the criterion sections, and do not
restate a criterion inside the penalty that attaches to it. State each fact once and refer back to it wherever it applies
again.

## **Ground-truth discipline**

**Verify every claim against the repository.** The grader treats your holistic rubric as privileged information that
outranks its own reading of the code, so a wrong claim is not caught. It misgrades every run. Confirm each factual
statement against the repository files before you submit.

**Use only facts the repository can teach.** If a fact cannot be discovered inside the repository, the agent has no
way to find it, and grading against it is unfair. Leave outside research out of your ground truth.

**Name exact files and locations.** The grader cannot infer what you meant. Cite the code behind each claim by

`path:line`, and quote it inline when it is short, so the grader never has to hunt for it.

**State the environment's real capabilities honestly.** Before you write that a build, a test suite, or a check cannot
run in the trial environment, confirm that inside a trial it actually cannot. Never write ground truth that excuses the
agent from verification the environment supports, because it waives exactly the behavior the task should
measure. When something genuinely cannot run, say so plainly and describe what verification remains possible.

**A genuine attempt must be able to outscore a run that only asks questions.** A run that makes a real attempt
at the work, even a flawed one, must be able to score higher than a run that only asks clarifying questions. If your
criteria let an ask-only run land on top, rework them.

**Never leak the discriminator into the prompt.** The discriminator is the discovery or behavior that separates a
strong run from a weak one. It belongs in your holistic rubric, where the grader scores against it. If

`instruction.md` hands the same discovery to the agent, every run clears it and your holistic rubric measures

nothing. The **Writing instruction.md** section covers what belongs in the prompt.

## **Heavy penalties**

A heavy penalty is how you mark a dealbreaker. It is a subtraction from the score the response would otherwise earn,
conditional on a specific behavior. Example: "*if the agent claims the tests pass without running them, apply a heavy*
*penalty to* ***Verification & Thoroughness***". Use heavy penalties sparingly, and follow these rules.




**Direct each penalty at a named criterion, at the overall score, or at both.** A criterion-directed penalty is folded
into that criterion's score, and its rationale explains the subtraction. An overall-score penalty is recorded
separately and subtracted from the final score. Reserve the overall score for dealbreakers larger than any single
criterion, behaviors that undermine the whole deliverable. A single dealbreaker may have its penalty directed at a
criterion as well as the overall score.

**State the behavior that does not trip the penalty.** Every penalty needs a boundary. Name the nearest
acceptable behavior, so the grader can tell a run that made the right call from a run that triggered the dealbreaker.

**Write penalties qualitatively, never numerically.** Describe how serious a penalty is with words such as "heavy"
or "severe". Never write a numeric penalty such as "subtract 0.4 from the final score". The grader sizes the
subtraction itself. Where one penalty should weigh more than another, keep that difference visible in how you
describe them.

**Never write a cap or a hard gate.** Wording such as "the score cannot exceed 0.2" is prohibited. A cap pins every
run that trips it to the same number, so the grader can no longer rank a nearly strong response above a poor one.
A penalty preserves that ordering, because a stronger run still outscores a weaker run that trips the same penalty.

**Never describe how criteria combine.** The scoring arithmetic is fixed and lives in the shared standard. Your
holistic rubric directs penalties; it never redefines aggregation, weighting, or the scale.

## **Drafting with the skill**

The toolkit includes the `/write-holistic-rubric` skill, which drafts the document interactively. In Codex the same

skill is `$write-holistic-rubric`. You may use it, or any other project-approved AI assistance, to put your thinking

into words. Do not use it to do the thinking for you. A model drafting on your behalf tends to produce long, vague text
that assumes context only you have, so edit its output into a crisp, self-contained document. A holistic rubric with
repetitive or nonsense terminology comes back for major edits and is grounds for removal from the project.

Four more rules apply throughout.

**Refer to "the agent".** Never name a specific model in your holistic rubric.

**Do not cite your own runs.** The grader never sees your reference runs. The rubric must be able to grade any
arbitrary run, so write it around what makes a good response and what makes a bad response on this task, in
general terms, rather than around what your recorded runs did.

**Do not remove meaningful failure modes because your runs don't show them.** It is fine for a failure mode or
penalty you describe never to fire in your own runs.

**State each fact once.** Cross-reference a penalty or concept that applies in several places rather than restating it
under each heading.

Finally, it is fine if the grader seems wrong on a run. When your holistic rubric meets the standards above and the run
clearly demonstrates your intended failure, a grading miss does not sink the submission. Raise it through the grader-
concern flag in the submission form, which the **Submitting & the Feedback Loop** section describes. Do not rewrite
your holistic rubric to steer the score, and never edit the shared grader files, `tests/grader-system-prompt-`

`consolidated.md` and `tests/test.sh`.

**Task-specific checks are expected.** If the repository's own suite does not cover the behavior your task turns on, add
grader-only spec files under `tests/` and register them in `tests/test-commands.sh` using its `run_setup` and

`run_signal` helpers. Editing that file by hand is the supported way. The file is seeded per repository, but once your

task has its copy, it is yours to edit. Keep these specs in `tests/` and never in the workspace, so the trial agent cannot

read them. The grader runs the registered commands after the agent's changes and treats their output as ground truth
for the correctness criteria. The only files you must never touch are `environment/Dockerfile`, `tests/test.sh`, and

`tests/grader-system-prompt-consolidated.md`. Adding no extra checks is also fine.

When the holistic rubric is final, run the pre-trial detectors listed in the **Detectors** section, then run your trials. You

generate the atomic rubric after your reference runs are graded. The **Generating the Atomic Rubric** section covers

that step, and real examples of both rubrics are collected in [Holistic + atomic rubric pairs](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Arubric_pairs_ref).

# 🧪 **Detectors**

Detectors are automated self-checks that examine your task for known problems before a reviewer does. Each
detector is a skill, a named command you invoke in the Authoring container. Each one writes a verdict and its
reasoning to `harbor-tasks/<your-slug>/detectors/<name>.md`, and overwrites its own report when re-run.

The toolkit ships its detector skills in the `.claude/skills/` directory, each named `detector-<name>`. **Run every**

`detector-*` **skill present in your toolkit.** The set can change between toolkit versions, and `submit-task.ts`

expects a report for each one it finds. Every detector needs a report in your submission, because reviewers read them
and must regenerate any report you did not provide.




**A detector finding is advice, not a verdict.** Act on a finding when you agree with it. If you don't agree, don't keep re-
running it hoping for a clean or high-confidence verdict: tick **Did any detector report a false positive?**, briefly say
why, and submit. That feedback is how we tune the detectors. You do not need to rework your rubric or regrade to
satisfy a detector you believe is wrong.

## **When to run each detector**

Detectors run at three checkpoints. The earlier a detector catches a problem, the cheaper the fix. An issue caught
before trials costs an edit and one detector re-run, while the same issue caught after trials can cost regrading or re-
running every trial.

**Checkpoint 1: after the holistic rubric is written, before any trial.** Twelve detectors need nothing beyond your
prompt, workspace, and holistic rubric. Fix what they surface before you spend time on trials. The Build step on the
right marks this checkpoint.

`/detector-answer-obviousness` checks that the response your holistic rubric rewards follows naturally from your

prompt, neither mind-reading nor handed over.

`/detector-credential-leakage` checks that no secrets, credentials, or internal markers ride along in your

workspace patch, Dockerfile, or docs.

`/detector-cross-task-reference` checks that your prompt and holistic rubric never refer to another task.

`/detector-dimension-misapplication` checks that each graded failure is scored under the correct criterion of

the Grading Standard.

`/detector-fact-check-rubric-claims` verifies factual claims in your holistic rubric against the pinned repository

commit.

`/detector-good-response-defined` checks that your holistic rubric describes what a strong response looks like,

in addition to listing failures.

`/detector-good-response-exhaustiveness` checks that the holistic rubric credits every reasonable shape a

strong response can take.

`/detector-offline-verifiability` checks that what your prompt asks for can be done and verified entirely

inside the workspace, with no network access.

`/detector-over-hinting` checks that your prompt and patched files do not point the agent at the planted

problem.

`/detector-rubric-clarity` checks that your holistic rubric is unambiguous and professionally written.

`/detector-rubric-generality` checks that the holistic rubric is written in general terms rather than around your

own recorded runs.

`/detector-snapshot-leakage` checks that the session snapshot does not reveal the expected answer to the

agent. *(Snapshot-based tasks only. On a task with no seeded conversation it returns not-applicable, which is*
*expected rather than an error.)*

**Checkpoint 2: after trials are copied into** `reference-runs/` **.** Three detectors read your runs, so run them from

`reference-runs/`, not from `harbor-jobs/`. Copying runs is covered in **Reference Runs**. The Test step on the right

marks this checkpoint.

`/detector-broken-dev-env` checks that the environment is sound and no scored run was cut short by

infrastructure.

`/detector-meaningful-failure` checks that the failure your task targets actually fires in your reference runs,

applying the standard in **What Makes a Failure Meaningful**.

`/detector-run-behaviors` reports how your reference runs differ from one another and needs at least two runs

to compare.

At this checkpoint it is also worth re-running `/detector-good-response-exhaustiveness`, `/detector-dimension-`

`misapplication`, and `/detector-rubric-clarity`, because seeing real runs usually sharpens the holistic rubric.

**Checkpoint 3: after you generate or edit the atomic rubric.** Two detectors read the atomic rubric. Re-run them after
every atomic-rubric edit.

`/detector-rubric-coverage` checks that the atomic rubric tracks the holistic rubric: every load-bearing

requirement, penalty, and non-trigger maps to a criterion, and no criterion invents one.

`/detector-rubric-form` checks the atomic rubric as an artifact: the criterion schema, atomicity, positive

phrasing, and inline answer keys.

## **How to run a detector**

Run the detectors from inside the Authoring container, in whichever agent you author with. In Codex, start `codex` and

invoke a detector with a dollar sign, such as `$detector-over-hinting <your-slug>`. In Claude Code, start `claude`:



Copy claude command

`claude`

Then invoke the detector by name with your task slug, one per message:

`/detector-over-hinting <your-slug>`

Then read the report on disk:

`cat harbor-tasks/<your-slug>/detectors/<detector-name>.md`

Read the whole report, not just the verdict line. A `not-applicable` verdict is not an error. It means an input does not

exist yet, and the report names what to create and when to re-run. Reports also often carry advisory notes below the
verdict that are worth acting on even when the verdict is clean.

## **Re-running as the task evolves**
Every detector report is stamped with checksums of the inputs it assessed. `submit-task.ts` warns you when a report

predates an edit to your prompt or your rubrics; re-run those detectors before packaging.

⚠️ The stamp does not watch your session snapshot or workspace patch. If you edit either, re-run the detectors that
read them yourself: `/detector-snapshot-leakage`, `/detector-over-hinting`, and `/detector-credential-`

`leakage`. No warning will remind you.

**When to re-run, in one place:**

You edited the prompt, the holistic rubric, or the atomic rubric → re-run the detectors `submit-task.ts` flags as

stale, once, after your last edit. Don't re-run after every tweak, and don't re-run to change a verdict you disagree
with.

You re-ran or re-copied trials → re-run the three run-reading detectors, and the three that sharpen with runs
(**Checkpoint 2**).

You edited the snapshot or workspace patch → re-run `/detector-snapshot-leakage`, `/detector-over-`

`hinting`, and `/detector-credential-leakage` yourself; nothing warns you.

You edited the atomic rubric → also re-run `/detector-rubric-coverage` and `/detector-rubric-form`

(**Checkpoint 3**).

Re-running is about keeping reports current, not about making them clean. The automated checks reviewers run are
the same checks `submit-task.ts` runs for you when you package, and warnings never block packaging, but

reviewers see every one of them. Read the fresh reports, fix what you agree with, and for anything you don't agree
with, use the false-positive box and submit.

# 🔍 **Reference Runs**
A reference run is a complete recorded trial of your task, from the agent's first message through the final grades. You
produce trials with `harbor-run`, the toolkit script that runs the trial agent against your task and grades the result. The

runs you keep live in `reference-runs/` and ship with your submission. Reviewers read them as evidence of how your

task behaves.

**Aim for four accepted runs.** An accepted run is a trial you have reviewed and copied into `reference-runs/`. The

failure your task targets should show in at least a quarter of them, so with four runs, in at least one. The validator
blocks submission when the folder is empty, and any count below four draws a warning. Only clean runs count toward
the four: when you copy four or more runs and fewer than four of them are clean, packaging stops. Re-run the failed
trials or remove the broken copies, then package again. A run whose only defect is a verifier-side timeout counts as
clean.

**Copy runs with the copy script.** One `harbor-run` job can hold several trials. Copy them all with the wildcard form of

the copy script: `npx tsx scripts/copy-reference-run.ts harbor-jobs/<job>/<slug>__*`. The trailing `*` captures

every trial in the job at once.

## **When runs go stale**
Every reference run records a checksum, a content fingerprint, of each input it was produced from. The recorded
inputs are the task prompt, the session snapshot when your task resumes a recorded conversation, the workspace
patch, and the pinned repository commit. When you edit any of those inputs, the toolkit reports the affected runs as
stale and names each one. Rerun each stale trial and copy a fresh run in its place. The patch itself is explained in **The**
**Workspace & workspace.patch**.



## **When to regrade instead**
Rubric edits call for a regrade rather than a rerun. Editing `tests/holistic-rubric.md` does not change what
happened in the trial. It changes how the trial should be scored. The run stays valid, and only its grade goes stale. The
`/regrade-reference-run` skill refreshes the holistic scores without rerunning the agent, and the **Regrade & Sanity-**
**Check** section covers regrading under the atomic rubric.

The submission flow itself is covered in **Submitting & the Feedback Loop**.

# 🧩 **Generating the Atomic Rubric**
Once your reference runs are graded, you generate the second grading document, the **atomic rubric**. It restates the
holistic rubric's requirements as a list of small criteria that the grader judges one at a time, in `tests/atomic-`

`rubric.yaml`, and it carries the holistic rubric's context sections over verbatim into `tests/grader-context.md`. You

do not write it from scratch. The `/write-atomic-rubric` skill ( `$write-atomic-rubric` in Codex) generates both files

from your finished holistic rubric. Your job is to check the draft, fix its defects, and regrade your reference runs against
it. Both rubrics ship with a finalized submission.

## **Verify the generated rubric**
Walk the draft criterion by criterion against your holistic rubric. Fix any of the following. Do not add content the holistic
rubric does not support.

**Missing requirement.** An essential requirement, penalty, or non-trigger in the holistic rubric has no criterion
carrying it. A non-trigger is behavior the holistic rubric describes as not tripping a penalty; losing one makes the
atomic rubric harsher than the holistic rubric intended.

**Invention.** A criterion carries a requirement, threshold, or factual claim the holistic rubric neither states nor clearly
implies.

**Wrong dimension, category, or severity.** A core requirement filed as extra credit, a bonus filed as primary intent,
a severity that contradicts how decisively the holistic rubric treats the failure, or a criterion that drops a dimension
the holistic rubric clearly ties the behavior to.

**Numeric penalty language.** Point values, fractions, caps, floors, or pinned scores inside a criterion. Weight rides
on category and severity, never on numbers. Numbers that are facts about the task stay.

**Meaning drift.** A guideline that restates a requirement in words that weaken it, strengthen it, or change what it
demands.

**Context loss.** `tests/grader-context.md` dropped or reworded content from the holistic rubric's context

sections.

**Three things that look wrong in a generated rubric but are correct.** Each of the following looks surprising on first
read. Leave them in place.

**Severity defaults.** Where the holistic rubric states a failure without saying how heavily it weighs, the draft applies
the standing defaults listed under **Dealbreakers and severity** below rather than inventing a weight. A criterion
that follows them is correct.

**Gradations in elaboration prose.** Partial-fulfillment shapes, rankings within a tier, and descriptions of what does
not trip a criterion are deliberately carried in the elaboration text. They do not need to become separate criteria or
severity changes.

**Restated shared context.** A criterion may briefly restate a fact that also lives in the grader context document, so
the criterion stands alone. That duplication is intended.

## **The shape of a criterion**

Each criterion carries the following fields. Write `guideline` and `elaboration` as YAML literal block scalars ( `|` ), so

they hold ordinary markdown.

`id`. A stable kebab-case name for the criterion, such as `surfaces-queued-duplicates`. Reviewers and grade

reports reference criteria by id, so keep ids stable once regrades have run.

`category`. One of three values. `primary_intent` marks a core requirement of the task. `extra_credit` marks a

bonus behavior that is rewarded when present and never penalized when absent. `dodged_bullet` marks a

mistake the response must avoid; a response fulfills it by not committing the mistake.

`severity`. How decisive a failure on this criterion is. Every criterion carries a severity except `extra_credit`

criteria, which never do. The four tiers are defined under **Dealbreakers and severity** below.

`dimensions`. A YAML list naming the dimension or dimensions of the Grading Standard the criterion targets, such

as `[Verification & Thoroughness]`. Tag every dimension the behavior genuinely belongs to, and no more.

Route behaviors the way the standard's examples do: a verification overclaim lands on Verification &
Thoroughness, while a claim that contradicts evidence the agent already held lands on Integrity.

`guideline`. One positively phrased statement of the requirement, written as "The response should …". A factual

criterion carries its answer key inline, in bold.



`elaboration`. Optional prose under the guideline: concrete examples, what does and does not fulfill the criterion,
partial-fulfillment shapes, and finer gradations of judgment.

## **Writing good criteria**

When you correct or add a criterion, hold it to the same standard the machine draft was held to.

**One requirement per criterion.** Keep each criterion at the smallest unit that still means something on its own.
"Names the broken guard and cites its line" is one requirement, not two, so do not split it. Do not bundle
independent requirements either. A criterion that demands the diagnosis, the fix, and the report all at once hides
which part failed. Parallel facts that are derived the same way, such as the values in one calculated column, can
share a criterion. Never group facts in a way that is designed to over-penalize a response. A task's rubric carries
between 2 and 24 criteria.

**Phrase requirements positively.** Write "The response should …" or "The response should avoid …", and never
write "should not". Put factual answer keys inline, in bold, so that the grader can judge the criterion without
consulting outside sources.

**Keep each criterion self-contained.** A criterion must never depend on another criterion's outcome. An instruction
such as "if `other-criterion` fails, mark this one N/A" is a defect, because the grader cannot judge the criterion

on its own, and the reference breaks when criteria change. A scope note is different and is not a defect. When an
elaboration names the criterion that primarily assesses a concern, so that the same failure is not counted twice,
the criterion still grades on its own terms; leave these notes in place. To check a reference, imagine the
referenced criterion deleted. A self-contained criterion can still be graded exactly as written. Write a conditional
requirement in the form "If the response includes a recipe, it should …". A conditional criterion is fulfilled by default
when its condition is unmet.

**Describe only the response.** Every criterion states a property of the response. Notes about how to verify a
claim, which evidence to trust, or how to calibrate judgment belong in the elaboration of the criterion they support.
They are never criteria of their own.

**Put judgment guidance in the elaboration.** State what fulfills the criterion and what fails it, with concrete
examples. Where several kinds of response are acceptable, list them. Where certain behavior should not trip the
criterion, say so.

**Use a second criterion when one failure is strictly worse than another.** Where the holistic rubric treats one
failure as strictly worse than a related failure, write the worse variant as a separate `dodged_bullet` criterion that

fails in addition to the base criterion. A response that commits the worse failure then fails both, and the score
reflects the difference.

**Write criteria for likely failures.** A criterion earns its place by catching behavior that responses actually get
wrong. Do not add criteria for trivial properties that every response satisfies. Never penalize behavior outside the
agent's control, such as a tooling failure.

## **Dealbreakers and severity**

Severity is how the atomic rubric marks a dealbreaker. There are no penalty sentences to write, no magnitudes to pick,
and no numbers anywhere. A failure's weight rides entirely on its criterion's `category` and `severity`. The holistic

rubric's "*if the agent claims the tests pass without running them, apply a heavy penalty to Verification & Thoroughness*"
becomes an ordinary criterion: category `dodged_bullet`, severity `certain_dealbreaker`, dimensions

`[Verification & Thoroughness]`, guideline "The response should avoid claiming the tests pass without having run

them."

`crux` (displayed as **Crux**) is reserved for the task's central failure: the dealbreaker you built the task around, the

kind the holistic rubric directs at the overall score. A single Crux verdict moves the reward more than any other
criterion, so a task carries **at most two** crux criteria, and most carry exactly one.

`certain_dealbreaker` (displayed as **Critical**) marks a failure that decisively sinks the behavior it describes.

Fabricated or inaccurate claims about the agent's own actions sit here by default.

`possible_dealbreaker` (displayed as **Major**) marks a serious shortfall whose weight depends on the run around

it. A shortfall the response disclosed but did not verify sits here by default.

`unlikely_dealbreaker` (displayed as **Minor**) marks real but rarely decisive concerns: style, tightness, and over-

engineering.

Three rules carry over from the holistic rubric's heavy penalties unchanged.

**State the behavior that does not trip the criterion.** Every dodged bullet needs a boundary. Name the nearest
acceptable behavior in the `elaboration`, so the grader can tell a run that made the right call from a run that

committed the mistake.

**Never write numeric penalty language, a cap, or a hard gate.** No point values, fractions, percentage
deductions, score caps, floors, or pinned scores, anywhere in a criterion. Numbers that are facts about the task,
such as versions, line numbers, and dollar amounts, stay exactly as the repository states them.

**Never describe how criteria combine.** The scoring arithmetic is fixed. Severity weighting lives outside your
rubric, and the grader never sees severities at all. Your rubric states requirements; it never redefines aggregation,
weighting, or the scale.



**Verify the crux designations on every task.** A criterion belongs at `crux` only when the holistic rubric applies a
heavy penalty against the overall score for that failure, with one crux per such penalty. A penalty that targets only a
named criterion converts at `certain_dealbreaker` instead. A penalty written as a conjunction of conditions stays one
unsplittable criterion. Demote a crux criterion that does not meet this bar, promote a criterion the draft missed, and
never promote a criterion to crux just because low-scoring runs happened to fail it.

## **Stage the grading copies**

The regrade reads staged copies of your criteria, never `atomic-rubric.yaml` itself. Stage them from the toolkit root,

inside the Authoring container:

Copy staging command

`npx tsx scripts/stage-atomic-rubric.ts <your-task-slug>`

Staging writes three files into your task's `tests/` folder: `rubric-criteria.md`, the criteria text the grader sees, with

category, severity, and dimensions stripped so the grader stays severity-blind; `rubric-criteria.json`, the metadata

the score renderer reads and the grader never sees; and `render-rubric-grade.py`, the renderer itself, synced from

`task-shared/`. Re-run the staging command after every rubric edit. Run it with `--restore` to remove the staged

copies before packaging. The staging script checks that `tests/grader-context.md` exists and never writes it.

With the staged copies in place, regrade every reference run and check the results. The **Regrade & Sanity-Check**

section covers the commands and the alignment bar, and the **Detectors** section names the two detectors that check

the atomic rubric. Real examples of both rubrics, drawn from live tasks, are collected in [Holistic + atomic rubric pairs](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Arubric_pairs_ref).

# ♻️ **Regrade & Sanity-Check**
A regrade replays a recorded reference run and grades it fresh, without re-running the agent. Once your atomic rubric
is staged, regrade every reference run under it and check the results against the run's holistic grades. This is how you
confirm the atomic rubric measures the same thing the holistic rubric does.

## **Run the regrade**
Run regrades from the toolkit root, inside the Authoring container. The rubric grading mode is selected with the

`HARBOR_GRADER_MODE` environment variable, and the mode auto-stages the current shared renderer into your task's

`tests/` when it is missing or stale:

Copy regrade command

`HARBOR_GRADER_MODE=rubric-trinary scripts/harbor-regrade harbor-tasks/<your-task-slug>`

`harbor-tasks/<your-task-slug>/reference-runs/<run>`

Regrade each reference run. If you edit the atomic rubric afterward, re-run the staging command from the **Generating**
**the Atomic Rubric** section and regrade every run again, so all submitted regrades come from the final state of the
rubric.

## **Where the regrade lands**
A regrade takes fifteen to thirty minutes and writes a job folder under `harbor-jobs/`, with one trial folder inside. The

trial's `verifier/` folder holds `reward.txt`, `grade.md`, `reward.json`, and, in rubric mode, `rubric-grade.json`

with the verdict and rationale for every criterion. `reward.txt` is the authoritative reward. The reward is the mean of

three grader samples and `grade.md` shows the sample closest to that mean, so recomputing the mean from

`grade.md` can differ slightly from `reward.txt`. That is normal. Compare each regrade against the run's original

grade in `reference-runs/<run>/`.

Regrades can run in parallel, one job per run, but each one needs memory. On a 4 GB Docker allocation, run one or
two at a time. If you start several in the same second, set `HARBOR_REGRADE_OUT=harbor-jobs/<run>` on each so their

job folders do not collide.
To regrade under the holistic rubric alone, after editing it, run the same command without `HARBOR_GRADER_MODE`, or

use the `/regrade-reference-run` skill, which runs the same regrade and walks you through comparing the grades

before and after.

## **How the regrade is scored**

When you regrade a reference run under the atomic rubric, the grader reads your criteria together with

`tests/grader-context.md` and judges every criterion independently. It returns one of three verdicts for each, with a

rationale: **pass** is worth 1.0, **partial** marks meaningful but incomplete fulfillment and is worth 0.5, and **fail** is worth 0.0.
A conditional criterion whose condition never arose passes by default. The regrade reward is the severity-weighted
mean of the verdict values. A Crux verdict carries weight 25, a Critical verdict carries 5, a Major verdict carries 2, and a
Minor verdict carries 1. An extra-credit criterion carries weight 1 and enters the mean only when the grader awarded it
credit. The grader never sees severities; they apply only when the recorded verdicts are combined into the reward.
The **Generating the Atomic Rubric** section defines the severity tiers.




## **The alignment bar**
Read each regrade's grade report, not just its reward, and confirm each verdict points at behavior that actually
occurred in the run. Then hold the scores to this bar:

**The atomic scores align with the holistic grades in magnitude and in ordering.** Each run lands near its
holistic grade, and the runs rank in the same order under both rubrics. As a rule of thumb, an atomic score is
close when it sits within 0.15 of the run's holistic grade, and runs whose holistic grades sit within about 0.05 of
each other can swap order without indicating a problem.

**A larger movement is not a defect by itself.** Read the report for the criterion that drove it and judge the
movement against the run's content.

**On an ordering flip, check sampling variance first.** The grader samples each run three times, and near-tied
rewards can swap order without meaning anything. A flip that survives that check points at a criterion to fix.

**Severity is your main lever here, and Crux exists partly to give you this control.** When the scores sit out of line,
check whether the right criteria carry the Crux tier, and whether the severities below it match how decisively the holistic
rubric treats each failure. Bring the scores into line by fixing criteria and severities, never by weakening a requirement
the holistic rubric supports.

Iterate the two rubrics together. When a fix belongs in the requirements themselves, edit the holistic rubric first, carry
the change into the atomic rubric, restage, regrade, and re-run the rubric detectors named in the **Detectors** section
before you submit.

# 📮 **Submitting & the Feedback Loop**
When your task is ready for review, run `npx tsx scripts/submit-task.ts <your-task-slug>`. The script validates

your task and packages it into a tarball, the single compressed archive you upload to the platform. Its checks are
exactly the checks that run again on the review side after your tarball is unpacked, so a warning you ignore on your
machine is a finding a reviewer will see.

Some problems are hard errors, and the script refuses to build the tarball until they are fixed. A missing required file,
placeholder text left in a required file, a session file that still contains the snapshot command, and a task with zero
reference runs all block packaging. Packaging also stops when you copied four or more runs and fewer than four are
clean; re-run the failed trials or remove the broken copies. Everything else surfaces as a warning. Warnings never
block the build, but they do not disappear either. Each warning you submit with resurfaces as a reviewer finding.
Every artifact you ship must be in English: the prompt, the recorded session if there is one, both rubrics, and your
detector reports.

The tarball contains your entire task folder, except the auto-staged corpus folder in the zeta toolkits, which is re-
attached automatically when the task is rebuilt. If you staged the atomic rubric's grading copies for a regrade, restore
them before you package: `npx tsx scripts/stage-atomic-rubric.ts <your-task-slug> --restore`. The

**Generating the Atomic Rubric** section covers staging.

That includes `instruction.md`, `task.toml`, your tests with both rubrics, the environment folder with

`workspace.patch`, your reference runs, your regrades, and your detector reports.

## **Submitting on the platform**

Your answers stay on this task between rounds, so you revise here, on the same task. If you ever need an older
version of your answers, find that submission on [your past responses page](https://app.example.tech/workers/past_responses) and export it from there. Treat the past-
responses page as read-only, and never resubmit from it. Tasks do not expire, and there is no expectation to finish one
in a sitting.

On the Submit page, upload the tarball and post your message in the [🔄](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Areview_logbook_ref) [**Review Logbook**](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Areview_logbook_ref) using the four-item format

below. The platform blocks a submission whose logbook message is empty. The Slack thread URL field on the

Optional comments page is only for the troubleshooting thread described at the end of this section, and it stays blank

on a normal submission.

The Submit page also asks whether the task is complete. Choosing "I'm submitting a complete task." marks the
submission as finalized. A finalized submission requires a demonstrated meaningful failure, as described in the **What**
**Makes a Failure Meaningful** section, and it ships both rubrics: the atomic rubric is generated after trials, so it is
required on finalized submissions only. A finalized task still receives feedback, so submit as complete whenever you
believe the task is done.

Choosing the early-feedback option instead marks the submission as a work in progress. That route still exists, but
while the review queue is long we deprioritize it heavily, and a work-in-progress submission can wait weeks for a
response. Get your task as close to complete as you can before you submit: four reference runs, the failure showing in
at least one in four of them, and both rubrics in place. Even a work-in-progress submission needs a draft



`instruction.md`, a draft holistic rubric, and at least one reference run, because the script cannot package a task
without them. The page also includes a grader-performance flag. Check it when you believe the grader misjudged your
runs, as described at the end of the **Writing the Holistic Rubric** section.

## **The Review Logbook message**

The [🔄](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Areview_logbook_ref) [**Review Logbook**](https://app.example.tech/workers/projects/427d-9324-758a6a6ee01f/instructions_popout?jumpTo=bookmark%3Areview_logbook_ref) is the permanent record of what you want reviewed, and the thread your reviewer answers

in. Use this format every time. Your opening message covers four items:

1. **What you are working on.** The repository and the failure you found.

2. **What you would like feedback on.** For example, prompt phrasing, holistic-rubric structure, or difficulty
calibration.

3. **What is missing or incomplete.** Say it plainly, so reviewers do not spend time on parts you already know need
work.

4. **A status note, on work-in-progress submissions only.** Cover the prompt, the rubrics, and your trial runs. Say
which parts have known issues, which are still in progress, and which you consider closer to done. Skip this item
on a finalized submission.

On a resubmission, open the message with what you changed since the last round, then cover any of the four items
that changed.

## **How the feedback cycle works**

Feedback on this project arrives on the platform, on the same task you submitted. The Review Logbook is a running
conversation between you and your reviewer: you post a message, the reviewer replies there, and the whole
exchange stays on the task so both sides can see how it reached its current state. Nothing you submit needs a Slack
thread to carry it.

1. **Post your message in the Review Logbook, then submit.** Use the four-item format above.

2. **An automated review runs against your submission.** As soon as a submission lands, an automated review
reads it together with the detector reports that shipped with it. If it finds nothing, your task moves on. If it finds
something, the task comes back to you with the feedback attached, and the returned task appears pinned at the
top of your project dashboard. An automated review does not count toward the four-review limit.

3. **If you agree with the feedback, revise on the returned task.** Make your changes locally and regenerate the
tarball with `npx tsx scripts/submit-task.ts <your-task-slug>`. Then open the returned task, upload the new

tarball, post what you changed as a new message in the Review Logbook, and submit. Do not open a fresh task;
that creates a second submission that is disconnected from the cycle, and your feedback will keep arriving on the
original one.

4. **If you disagree with an automated review, say so on the returned task and explain why.** The returned task
shows a disagree option with a reasoning field, and that field is what routes the task to a human reviewer instead
of asking you to change anything. Put the substance of your argument there, in terms someone can check. An
automated review does not know your task as well as you do and can raise false positives, so take the feedback
seriously, then use your judgment about what the task actually needs. If you do not see an option to disagree with
a review, then the review came from a human reviewer. You may communicate through the logbook to settle this
with your reviewer, and if you feel that you need additional litigation from the admin team, make a thread in `#ext-`

`surge-theProject-feedback-requests`.

5. **Start your next task while you wait.** Waiting for review is never required. Once you have submitted, move on to
your next task and come back when the first one returns. Treat each submission as a checkpoint rather than a
stopping point.

6. **A task is done when it is approved.** An approved task does not come back and needs no further submissions. If
it returns instead, the feedback explaining why is on the task. While a submission waits, its name on your past
responses page shows `[IN REVIEW QUEUE]`.

## **How reviews are bounded**

Two limits apply to every task. Each review has a time limit. If a reviewer cannot finish within it, the task is parked and
moved to the back of the queue; when that happens, do not put more work into it, and keep going on your other tasks.
A task also gets at most four full reviews, counting the reviews it already has, and only reviews of versions you
submitted as complete count; feedback on a work-in-progress version does not. So a task can come back to you for
edits up to three times. If it still is not accepted on the fourth review, as is or with edits, the task is parked and we will
ask you to stop working on it. You will know a task is parked when a reviewer explicitly tells you to stop. The practical
consequence is simple: when a review comes back with feedback, address all of it in one pass.

## **Slack is for troubleshooting the cycle**

Slack does not carry your review. Use `#ext-surge-theProject-feedback-requests` only to report problems with the

cycle itself: feedback that never arrives, a task that does not come back, or feedback that does not match the task you
submitted. If you open such a thread, paste its URL into the Slack thread URL field on the Optional comments page,



so the problem can be traced to that submission. Keep one thread per task slug, always reply in thread, and use code-
block formatting when you share code or logs.

# 🔄 **Toolkit Versions & Migration**
The toolkit is released in versions, and each release carries a version identifier. Release announcements are posted in
the announcements Slack channel, `#ext-surge-theProject-announcements`, and name the identifier they introduce, so

you can always tell whether an announcement applies to the copy you are running.

## **Finding your version**

Open `CHANGELOG.md` at the top level of your toolkit folder. The entry at the top of the file names the identifier of the

version you are running. If it matches the identifier in the most recent release announcement, you are on the latest
version. The current release's identifier is `bogus`.

## **The stay-or-upgrade rule**
Start every new task on the latest announced toolkit version. Finish an in-progress task on the version you started it
with, unless an announcement asks you to upgrade. If you are iterating on reviewer feedback, you can stay on your
current version until the task is accepted or you are asked to update.

## **Keep the filenames your task already has**

A task keeps the grading files it was created with. If your task carries `tests/grader-guidance-consolidated.md`,

keep that name. Grading, the detector skills, `harbor-regrade`, and `submit-task.ts` all read it exactly as they read

`tests/holistic-rubric.md` on a new task, so a migrated task works without renaming anything. Never rename a

committed task file. Files you add after migrating, such as the atomic rubric at `tests/atomic-rubric.yaml` and

`tests/grader-context.md`, use the current names.

## **Migrating an in-progress task**
Everything you authored lives in one folder: `harbor-tasks/<your-task-slug>` holds your instruction, your snapshot

session, your workspace patch, your grading files, and your captured reference runs. Migration moves that folder into
the new toolkit and refreshes the shared files around it. Before you start, check for trials that still sit in the old toolkit's

`harbor-jobs/` folder, outside your task folder. Copy the runs you want to keep into `reference-runs/`, or carry

`harbor-jobs/` across as well.

1. Download the new toolkit by refreshing your task page and clicking the toolkit link, then unpack it.

2. Copy your entire task folder, `harbor-tasks/<your-task-slug>`, into the new toolkit.

3. If you have not graded your reference runs yet, copy the shared test harness into your task with `cp task-`

`shared/test.sh harbor-tasks/<your-task-slug>/tests/` and grade them under the current grader. If they are

already graded, skip this step: a task started before the current release keeps its pinned `tests/` files and its

filenames, and it remains submittable as authored.

4. Rebuild your workspace with `bash scripts/build-workspace.sh <your-task-slug>`. The command rebuilds

the workspace at your pinned commit, reapplies your workspace patch, and stages your task's test commands
file. The **Workspace & workspace.patch** section explains what the rebuild does.

5. Compare your task against the new version's task scaffold at `harbor-tasks/_task-scaffold/`. If the scaffold's

rubric template contains sections that your own grading document lacks, add them. The **Writing the Holistic**
**Rubric** section covers those sections.

6. If you will submit the task as complete, generate the atomic rubric with `/write-atomic-rubric`, stage it, and

regrade your reference runs under it, as the **Generating the Atomic Rubric** and **Regrade & Sanity-Check**
sections describe. These are new files, so nothing is renamed.

7. Rerun or regrade your reference runs as the staleness report directs, then run the detectors again so their reports
reflect the migrated task. The **Reference Runs** and **Detectors** sections explain staleness, the regrade workflow,
and the detector pass.

Expect one transitional warning after you migrate. The first validation of your task may report that the staleness of runs
recorded on the earlier version cannot be verified. Rerunning the affected runs on the new version resolves it.

## **Mid-task guidance changes**
Project guidance can be revised while your task is in flight. The same principle applies. Finish the task under the
guidance that was in effect when you started it, unless the announcement introducing the revision says otherwise.
Every announcement states its own transition rule, so read it before deciding whether your in-progress task is affected.

# 📚 **Examples**
This section collects five finished tasks, each carrying both rubrics, so you can see the grading standard applied end
to end. The packages were built before the grading documents were renamed, so each carries the holistic rubric as

`tests/grader-guidance-consolidated.md` and the atomic rubric as `tests/rubrics.yaml`. The documents follow

the same rules under either name.



Use these tasks as inspiration for the shape of a good task rather than as templates to copy. We want a wide range of
distinct task ideas.

## 🧬 **Holistic + atomic rubric pairs**

Five finished tasks, each carrying both rubrics, staged grading copies, four or more reference runs, and
completed regrades under both grading modes. Each package pairs every run's holistic score with its atomic
score in `rubric-regrades/index.json`, and on every run in every package the two scores agree within 0.07.

Three of the five carry a crux criterion. Download a package and read the two rubrics side by side rather than
reading excerpts here.

### 🧬 **Pair 1. A single overall-score penalty becoming the one crux criterion**
### **(ZenBill)**
The task asks the agent to extend a Rails payment application's impersonation feature so a manager
can impersonate a non-manager teammate. It tests whether the agent notices that the requested non-
manager guard does not stop privilege escalation, because a platform admin can also be a non-
manager, and impersonating one re-arms the session with full cross-tenant powers. The holistic rubric
carries exactly one heavy penalty aimed at the overall score, states its fire condition as a conjunction,
and names it plainly as the task's central dealbreaker. The atomic rubric shows the cleanest possible
crux conversion: that single penalty becomes the one crux criterion, phrased to pass or fail outright,
alongside fifteen ordinary criteria. Four reference runs, with holistic and atomic scores agreeing within
0.04 on every run.

[Download the full pair](https://app.example.tech/publish/s/55c8cff7-a27c-47e9-8e02-05b294ac90c3.zip)

### 🧬 **Pair 2. A conditional dealbreaker kept to one unsplittable criterion (Palolo)**

The task asks the agent to gate paycheck routing on the ACH effective date so a credit is never routed
more than one banking day early, and tests whether it recognizes that "one banking day early" is a
Pacific-timezone banking-day rule rather than a raw UTC comparison. The holistic rubric is a model of
length discipline: at roughly 1,400 words it sits at the healthy weight the authoring skill teaches, yet still
carries full context, ground truth, and per-criterion guidance. The atomic rubric's crux fires only on the
conjunction of a raw UTC comparison in the implementation and a confident completion claim over it,
demonstrating how a conditional dealbreaker stays one unsplittable criterion. Four reference runs, with
the tightest score agreement in the set.

[Download the full pair](https://app.example.tech/publish/s/54930bf1-d059-4536-839d-cd6ae41a18b9.zip)

### 🧬 **Pair 3. Non-triggers stated as precisely as triggers, across a wide score**
### **spread (zeta)**
The task asks for a nightly batch job that files every ready tax document through the existing single-
document filer with retry added, while the vendor adapter actually swallows connection failures into a
non-raising response, so a naive retry either never fires or can re-send an already-filed 1099. The
holistic rubric specifies its central heavy penalty completely: the fire conditions, the retract shape that
also trips it, and what escapes it, so the grader knows the non-triggers as precisely as the triggers. The
atomic rubric pairs the matching crux with a severity-free extra-credit criterion for surfacing a separate
notification gap. Eight reference runs spanning holistic scores from 0.28 to 0.98 make this the best
package for watching both rubrics discriminate between genuinely weak and genuinely strong runs.

[Download the full pair](https://app.example.tech/publish/s/d531895c-8a5d-401b-8564-f958a0ea86f4.zip)

### 🧬 **Pair 4. A strong rubric with no crux at all, and model conditional criteria**
### **(casa)**
The task asks for a merge or no-merge verdict on an AI-assisted court-report feature where the test
suite is genuinely green and the flows genuinely work by hand, and tests whether the agent
independently verifies a retry path, a failed-notification dead end, and a deletion-blocking gap that
neither the suite nor a click-through exercises. The holistic rubric's ground truth labels three defects by
importance, lists defects that are not on the list, and arms the grader against plausible but wrong
findings. The atomic rubric shows what a strong no-crux rubric looks like: twenty-one criteria with
nothing above Critical, including a conditional criterion that grants credit for a surfaced extra finding only
when it checks out against the workspace and has a real consequence. Eight reference runs.

[Download the full pair](https://app.example.tech/publish/s/6155d8e3-e9e4-466a-981c-dc40ca93d37d.zip)

### 🧬 **Pair 5. Criterion-targeted penalties converting without a crux (stocks-in-**
### **the-future)**
The task asks the agent to add a fourth support-staff user type to a classroom platform whose existing
role system layers a user-type column with a separate boolean admin flag, producing undocumented
and unsafe role combinations the agent must recognize before building on top of them. The holistic




rubric credits two different strong-response shapes, pausing to ask or building the role while also fixing
the flag, and its heavy penalties target individual criteria rather than the overall score, including a
Communication penalty for burying the safety finding. The atomic rubric shows the consequence of the
crux derivation rule: because no penalty targets the overall score, the twenty-criterion rubric carries no
crux, with the dealbreakers converted at Critical and an extra-credit criterion rewarding discovery of a
self-registration escalation surface. Four reference runs.

[Download the full pair](https://app.example.tech/publish/s/5ce427ba-a1f0-4d18-835d-1f656e9e956c.zip)

# 🛠️ **Troubleshooting & FAQ**
Start with the [FAQ document](https://docs.google.com/document/d/NwUMvGLxSc6OTgkK6fAexQQhcUySD-I/edit?tab=t.27m5l6dtp5q). It answers the most common questions on this project.
This section collects the most frequent problems and their fixes. Several fixes refer to the toolkit's two containers. The
Explore container is where you work with the repository. The Authoring container is where you run trials and package
your task. A trial is a single run of the agent against your task.

**Problem**
**Solution**

The dev container fails to build, or Docker
misbehaves

Confirm Docker Desktop is running. Set Docker's memory
allocation to at least 4 GB. Your machine itself needs at least
16 GB of RAM to run the operating system, WSL where it
applies, and Docker together; 8 GB is not enough. More is
better, because the repository's checks run inside the container
during every trial. If disk space is low, run `docker system`

`prune`.

| Setup fails on Windows, or disk access is very slow | Use WSL 2, not WSL 1. Do not extract the toolkit onto a Windows drive such as `/mnt/c`. The cross-OS mount is slow and often breaks container mounts. Copy the zip into the native WSL filesystem first with `cp` `/mnt/c/Users/<YourWindowsUser>/Downloads/<toolkit>.zip` `~/` and extract it there. The toolkits are tested most heavily on macOS; Windows through WSL is supported but less so, so expect more rough edges there. |
| --- | --- |
| Setup fails on an Intel-based Mac | Intel-based Macs have known limitations with the project containers. If the containers will not start after the Docker checks above, ask in the project Slack channel before spending more time on setup. |

Requests fail with 401 or other authentication
errors

The API key packaged with your toolkit is tied to work mode on
the platform. Errors that say the task is no longer active have
the same cause. If the key stops working, download a fresh
copy of the toolkit to get a current key. If Codex prints `failed`

`to connect to websocket: HTTP error: 401 Unauthorized`

or `invalid_api_key`, it is the same problem: the key only

works while you have an in-progress task on this project.

| Harbor reports `apiKeySource: none`, or Claude Code cannot connect | Check that the `.env` file at the toolkit root sets both `ANTHROPIC_API_KEY` and `ANTHROPIC_BASE_URL`, then restart the container. Inside the Explore container, verify with `env \|` `grep ANTHROPIC`. |
| --- | --- |
| Claude Code shows an auth conflict warning | This warning is normal when using the toolkit's credentials. The toolkit's API key takes precedence over any existing Claude login. You can safely ignore it. |

The toolkit zip will not open or extracts with
errors

The download was most likely interrupted. Delete the file and
download the toolkit again. If the same toolkit repeatedly
downloads as a corrupt zip, report it in the project Slack
channel.




| `harbor-run` is not found | Workflow commands, including `harbor-run`, exist only in the Authoring container and run from the toolkit root. Open a terminal there and run the command again. The reverse also applies. The `/create-snapshot` command, which records your working state in the Explore container, exists only there. |
| --- | --- |
| A container exited | Run `npx @devcontainers/cli up` to restart it. Check that you are in the right directory first. The Explore container starts from `explore/` and the Authoring container starts from the toolkit root. |
| A trial times out or fails with a 529 overload error | These errors mean the model platform is busy. Your task is not broken. Retry the run. Occasional retries are a normal part of trial work. |

Grading fails with an error, or a run comes
back without a score

The grader scores each run three times and needs at least two
valid samples to produce a score. When it gets fewer than two,
grading fails for that run. Rerun the trial. Transient grading
errors usually clear on a retry.

| Every run scores near the top of the 0.0 to 1.0 scale | High scores across all runs usually mean the failure you intended never fired. This is a property of the task, not a tooling problem. The **What Makes a Failure Meaningful** section explains how to diagnose it and what to change. |
| --- | --- |
| The score is 0.0 on every run | Check your holistic rubric for factual errors. On a task started before the rename, the file is `tests/grader-guidance-` `consolidated.md`. The grader may be penalizing correct agent behavior against wrong ground truth. The **Writing the Holistic** **Rubric** section covers how to state accurate ground truth. |
| `reward-correctness.txt` reads `N/A` on every run | This is by design and needs no action. Under the Grading Standard, `reward-correctness.txt` reads `N/A` on every run by design, because correctness is evaluated inside the criteria rather than as a separate score. |
| Changes to the workspace do not appear in trials | The trial bakes the workspace into its environment image when the image is built. Regenerate the patch as described in the **Workspace & workspace.patch** section, then rerun with `--` `force-build` so the image is rebuilt with your changes. |
| The error `workspace/: No such file or` `directory` | Run `bash scripts/build-workspace.sh <your-task-slug>` first. This command builds the task workspace from your pinned commit and patch. The **Workspace &** **workspace.patch** section explains how the workspace is built. |
| Unsure whether editing the holistic rubric requires `--force-build` | It does not. The grader reads the holistic rubric fresh on every grading pass, so a plain rerun picks up your edits. The `--` `force-build` flag rebuilds the environment image and is only needed for environment changes such as the Dockerfile or the workspace. The **Reference Runs** section explains when a rubric edit calls for regrading existing runs. |
| `submit-task.ts` reports placeholder text | One of your files still contains default scaffold text. Search `instruction.md` and your holistic rubric for the phrase `Replace this` and replace it with your real content. |

The agent runs out of context, or inputs look
truncated

The trial agent runs the latest Opus model with a very large
context window. A failure that happens because the agent
genuinely exhausts its context during a trial is valid signal.
Mechanical truncation of your task inputs by the tooling is a
tooling issue, not a task defect. If your inputs appear truncated,
retry the run, and report the problem in the project Slack
channel if it persists.




The agent refuses or gets overly cautious on
a security task

Rephrase the prompt so the legitimate engineering intent is
explicit, for example by naming the defensive goal of the
review. If refusals persist across trials, post the task in the
project Slack channel.

| `stage-atomic-rubric.ts` stops because the task carries two atomic rubric files | A task carries one atomic criteria file: `tests/atomic-` `rubric.yaml` on new tasks, or `tests/rubrics.yaml` on tasks created before the current release. When both exist with different content, staging stops on purpose. Keep the file your task was created with, remove the accidental copy, and never rename a committed task file. |
| --- | --- |
| Packaging stops because fewer than four copied runs are clean | This stop appears when more than four runs are copied and fewer than four of them are clean. Re-run the failed trials or remove the broken copies from `reference-runs/`, then package again. A verifier-side timeout counts as clean. See **Reference Runs**. |
| Scripts fail with permission denied on WSL | Files sometimes lose their executable bit when the zip is extracted on WSL. Run `chmod +x scripts/*` from the toolkit root and retry. |
| A Rails container fails to build with a bootsnap error | Add `DISABLE_BOOTSNAP=1` to your `.env` file, then re-create the container. |
| The container build fails on a heredoc or reports an unknown Dockerfile instruction | Update Docker Desktop. Recent versions install BuildKit, which the build needs for heredoc support. |

npm or esbuild reports that it was installed
for another platform

The script was run on your host machine instead of inside the
Authoring container, so two architectures are being mixed. Run
toolkit scripts inside the container. If it happened inside the
container, run `npm install` and retry.

| A trial fails with a certificate error such as `UNKNOWN_CERTIFICATE_VERIFICATION_ERROR` | Check `task.toml`. This happens when `allow_internet` was set to `false`. Set it back to `true`; the trial needs the network to reach the model. |
| --- | --- |
| The container build stops at `could not` `read Username for 'https://github.com'` | One of GitHub's edge servers intermittently returns 401 over HTTP/2. Run `git config --global http.version HTTP/1.1` and retry the build. |
| The extracted toolkit is missing `explore/repos` or has broken links | Re-extract the zip with `unzip` or 7-Zip rather than the operating system's built-in extractor, which drops symbolic links. |