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quickchataiquickchatai/quickreview/skills/companion/replay/SKILL.md

replay

Skill9 starsChanged 29 days agoMITView on GitHub

Re-run a past episode offline against the committed regression case set — real human findings on closed PRs — to see how a proposed change to the reviewer would have behaved. Use when asked whether a tweak would still catch what humans caught, to calibrate against the pre-bot corpus, or to try a change before it lands. Strictly offline: it never labels a PR, never wakes a session, and never posts anything.

6 other projects use a version of this.

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The file

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We split this skill into the rules it gives an agent

16 rules. 0 are common, 10 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 10

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never label, re-label, or ask anyone to label a PR.

    line 23
  2. Distinctive:

    Never write an overseer inject asking for a re-review, a rerun, or a fresh round on any PR.

    line 24
  3. Very specific:

    Never touch dry_run. It is the owner's alone in both directions (docs/ownership.md), and a replay that needs it flipped is a replay you …

    line 26
  4. Distinctive:

    Never replay an open PR at all, whatever the mechanism.

    line 28
  5. Distinctive:

    no case is a still-open PR.

    line 37
  6. Very specific:

    no case is at or after the contamination cutoff (2026-03-01) — rows from then on are the old /auto-review loop's own output or suspected …

    line 38
  7. Very specific:

    A failure is an INVESTIGATION, not a veto and not a bug: Every finding carries an expectation label — expected-catch (the reviewer should …

    line 65
  8. Very specific:

    A label may be wrong: If the honest answer is that we do not want a finding raised, re-label the case out-of-remit with a note — but that …

    line 111
  9. Distinctive:

    Do not write a memory entry for a run.

    line 123
  10. Distinctive:

    Never label a PR, ask for a round, or nudge a session to produce a replay.

    line 128
  11. Distinctive:

    Never replay an open PR, or a case at or after the contamination cutoff.

    line 129
  12. Very specific:

    Never run against a gate that is not dry-run, and never change dry_run.

    line 130
  13. Distinctive:

    Never treat a run as a gate, a score, or permission to land — it has no blocking verdict by design.

    line 131
  14. Distinctive:

    Never widen the substance bar, drop the per-reviewer cap, or re-label a case to make a run come out better.

    line 133
  15. Distinctive:

    Never report a run you did not complete, and never present a vacuous run as a clean one.

    line 135
  16. Very specific:

    Never call GitHub, the mutation gate, deploy.sh, or the VM.

    line 137

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Replaying a past episode

This file is the doctrine; the case set was decided with the owner. The instrument itself is src/regression.ts, and where this file and that module disagree, the module wins — its assertions run, this prose does not.

The safety point, first, because it is the one that can do damage

A replay must never become a posting path.

There is an obvious way to "re-run a review": put the trigger label on the PR and let the live daemon dispatch a round. That is how the old cutover comparison harness worked, and it is forbidden here — a live round posts a real review to a real author on a real PR. The same applies to every disguised version of it:

  • Never label, re-label, or ask anyone to label a PR.
  • Never write an overseer inject asking for a re-review, a rerun, or a fresh round on any PR. Your one lever is not a replay mechanism.
  • Never touch dry_run. It is the owner's alone in both directions (docs/ownership.md), and a replay that needs it flipped is a replay you must not run.
  • Never replay an open PR at all, whatever the mechanism.

src/regression.ts enforces the same thing in code rather than in prose, and it is worth knowing exactly what it checks, because those checks are your floor and not your ceiling. assertReplaySafe(cases, gate) refuses to start unless:

  1. the gate it was handed reports dry-run — read from the object, never from config.toml, never inherited, never a printed sentence (see src/compare.ts's attestDryRun for what that mistake looked like);
  2. no case is a still-open PR;
  3. no case is at or after the contamination cutoff (2026-03-01) — rows from then on are the old /auto-review loop's own output or suspected AI-assisted, so scoring against them scores the reviewer against itself.

runRegression calls it regardless of whether you did. And the replay seam in RegressionDeps carries the rule in its own doc comment: it must build its own round in a scratch root against case.headSha, and it must not label a PR and let the live daemon dispatch. Nothing in that module imports the daemon, wire.ts, or a GitHub adapter — if you find yourself adding such an import to make a replay work, stop: that is the boundary, and you have just reached it.

What the set is, and what it deliberately is not

The cases are real findings by human reviewers on closed PRs (tests/fixtures/regression-cases.json, built by scripts/build-regression-set.mjs from the corpus export — by hand, never by a test and never by the daemon).

Three properties decide how you read a run:

  1. Selection is by SUBSTANCE, not by verdict. selectCases never reads the GitHub verdict — blocking measures the reviewer, not the finding, and 82% of blocking findings carry no correctness vocabulary at all. A finding is admitted only if it states a reason or proposes a concrete alternative (rung ≥ L3), is in English, is not bot-authored, and does not rest on evidence off the PR. Do not "improve" a run by widening that bar.
  2. A failure is an INVESTIGATION, not a veto and not a bug. Every finding carries an expectation label — expected-catch (the reviewer should reach it), out-of-remit (ratified design puts it outside the reviewer, so a miss is correct), expected-divergence (the human was argued down; either answer is defensible). Two of the three make a divergence the expected outcome. runRegression never returns a blocking verdict and its exitCode is always 0.
  3. There is deliberately no score to maximize. A set that could be optimized would ratchet the reviewer toward imitating one person's habits, and one reviewer is 43% of the corpus. If you catch yourself tuning a change until the numbers go up, you are doing the thing the set exists to prevent.

Running one

  1. Name the change under test — pass it as changeUnderTest. A run whose header cannot say what was tried is a run nobody can act on later.
  2. Load and parse the set with parseCaseSet. It refuses an empty or half-parsed set on purpose: a clean score out of nothing is the one result this whole module exists to make impossible.
  3. Supply a replay implementation that satisfies the rule above, plus the real gate object. If no offline replay implementation exists yet, say so and stop. "I could not run it offline" is a correct and complete answer; reaching for the live daemon to fill the gap is not. There is no almost-offline route.
  4. Run it serially. You have no subagents — cases run one after another, and runRegression already loops that way. Do not fake parallelism and never claim a run you did not do.
  5. Read renderInvestigation's output as written. It opens by saying what it is not, because the one way this set can do harm is by being read as a pass/fail gate the reviewer is then tuned to satisfy.

Reading the result honestly

  • not-reached is the only column worth investigating, and the question it asks is not "is this a regression?" but "is this in the reviewer's remit at all — and if it is, was it ever reached before this change?" A finding unreached both before and after is not evidence about the change.
  • vacuous cases — the replay produced nothing at all for a case that has findings. Suspect the harness before the reviewer. A vacuous PASS from an extractor that matched nothing was the old comparison harness's failure mode; when half the cases are vacuous, runRegression says ask-owner and it means it.
  • Reviewer skew above 40% means the run is partly measuring one person's habits. Widen the set before acting on a pattern in it.
  • sandbox-only findings are not failures. The reviewer reads things humans skipped, and that is what it is for.
  • A label may be wrong. If the honest answer is that we do not want a finding raised, re-label the case out-of-remit with a note — but that is a change to the instrument, so it lands like any other change: through the ratifying turn, via land.

After the run

Report the recommendation (no-action, look-at-these, ask-owner), the headline, and the unreached findings — in the column, in the owner's own terms. A run never decides whether the change lands. It is one input to the argument that happens before land is ever loaded, and it does not replace it.

Do not write a memory entry for a run. The investigation markdown is the artefact; a run is a measurement, not a conclusion.

Never

  • Never label a PR, ask for a round, or nudge a session to produce a replay.
  • Never replay an open PR, or a case at or after the contamination cutoff.
  • Never run against a gate that is not dry-run, and never change dry_run.
  • Never treat a run as a gate, a score, or permission to land — it has no blocking verdict by design.
  • Never widen the substance bar, drop the per-reviewer cap, or re-label a case to make a run come out better.
  • Never report a run you did not complete, and never present a vacuous run as a clean one.
  • Never call GitHub, the mutation gate, deploy.sh, or the VM. The corpus, the case set and the reviewed code are all local files.

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