---
name: detector-run-behaviors
description: |
  Self-check the diversity of your task's reference runs by pulling out a
  small set of discriminating behavior axes — named behaviors that
  distinguish runs from each other (framing choices, hallucinations,
  citation style, etc.) and emitting a structured behaviors × runs
  matrix. Useful as a sanity check before submission: if your reference
  runs all behave identically along every dimension you can name, the
  task probably isn't discriminating enough.
allowed-tools: Bash, Read, Write
---

# Run-behaviors extractor

This skill helps you see how your reference runs differ from each other.
It pulls out 5–10 behavior axes — named behaviors that distinguish
runs from each other (framing, investigation depth, hallucinations,
citation style, hedging) — and writes a structured matrix you can use
to confirm your task is producing genuinely diverse failure modes.

**This skill needs at least 2 reference runs.** Run your task with
`scripts/harbor-run harbor-tasks/<slug> -k 4` (or similar) first so there
are multiple `grade.md` and `answer.md` files to compare; with fewer
than 2 runs there's nothing to discriminate against and the detector
returns `not-applicable`.

Read these before starting:

1. `.claude/skills/_detector-worker-shell.md` — where to write the report and how to handle re-runs. Detectors with structured payloads (this one's `runBehaviors` matrix) embed them in the same frontmatter block as `detector`/`verdict`/`confidence`.
2. `.claude/skills/detector-run-behaviors/core.md` — what makes a good behavior axis, the structured `runBehaviors` payload shape, verdict enums, body sections.

Compose the report per the schema in `core.md` and write it per `_detector-worker-shell.md`.

## Acting on the verdict

- **`summary`** with `HIGH` confidence — your runs differ along clear,
  named axes. Good: that's the signal that says your task is
  discriminating enough to produce a useful score distribution.
- **`summary`** with `MEDIUM` or `LOW` confidence — your runs look
  similar to each other and the axes you pulled out feel forced. The
  task may not be producing enough diversity to be a meaningful
  benchmark. Consider whether the prompt is too prescriptive, or
  whether more reference runs would surface real variation.
- **`not-applicable`** — fewer than 2 reference runs. Run more trials
  first.