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trac3r00trac3r00/agent-skills/skills/pro-review/SKILL.md

pro-review

Skill0 starsChanged 3 months agoMITView on GitHub

Explicit second-opinion code review: scope the change set, hand a sized, hazard-filtered brief to ChatGPT Pro (default, through a pinned guarded browser transport) or to a real agent client (OmO, Claude, Codex) in its own Herdr pane, then machine-check the returned report and verify every finding locally. Use only when invoked as /pro-review, $pro-review, or /skill:pro-review.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 5 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use this workflow when explicitly invoked as /pro-review, $pro-review, or /skill:pro-review.

    line 14
  2. Distinctive:

    Default engine: the Pro engine reaches the web-only ChatGPT Pro tier through the pinned, guarded transport.

    line 70
  3. Distinctive:

    Run that through the background command monitor with a deadline covering the 20-minute response allowance.

    line 79
  4. Distinctive:

    Wait for the report file the brief named - watch that path, or wait on the client's own settled state when Herdr tracks it.

    line 107
  5. Distinctive:

    If a client stalls, sits on an approval dialog, or loses its transport, recover the same pane or session rather than submitting a duplicate.

    line 125
  6. Distinctive:

    Read the report artifact. Reproduce each proposed finding in the current code and run focused checks where needed.

    line 132

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

OmO Pro Review

Use this workflow when explicitly invoked as /pro-review, $pro-review, or /skill:pro-review. It obtains an independent review from a real agent client that inspects the project itself, machine-checks the returned report, and verifies every claim locally before reporting. It adds no model, provider, or auth configuration, and it is not a substitute for tests.

The /pro-review prompt alias tells the host agent to read this file; native $pro-review and /skill:pro-review invocations expand the skill directly.

1. Scope the question

State the review question in one sentence. Use the user's target and its absolute paths or globs. Without a target, review the current working changes plus their callers and tests. If neither exists, ask what should be reviewed. Never hand a reviewer the home directory, an entire workspace, or unrelated personal data as a guessed target.

Inspect the implementation yourself first so you can brief the reviewer accurately and judge its answers later. Scope to the complete relevant set: full function bodies, callers, types, tests, and configuration. A diff alone is rarely enough. For a contained feature name its whole module; for larger work trace dependencies and boundaries instead of widening to the whole repository.

2. Plan the handoff

PRO_REVIEW_DIR below is this skill's own directory (for example ~/.agents/skills/pro-review, or wherever your client installed it). The scripts need Node.js 24 or newer and nothing else.

Let the handoff engine do the mechanical scoping, sizing, hazard exclusion, and pass splitting, then read its summary before sending anything:

node "$PRO_REVIEW_DIR"/scripts/handoff.mjs plan \
  --repo "$PWD" --changes \
  --question "<the one-sentence question>" \
  --out "$PWD/.pro-review/<slug>"     # the default engine is ChatGPT Pro

It writes manifest.json plus one brief-pass<N>.md per pass and prints a scoped summary: files with roles and token estimates, every exclusion with its reason, the git digest (including deleted paths), the report path, and one nonce marker per pass. The path policy is a bounded filter on path shape (secrets, tokens, cookies, sessions, logs, generated and excluded directories, earlier handoffs); it does not detect credentials pasted inside ordinary source files. The output directory must be new or empty; --force replaces only an earlier handoff's own manifest and briefs, and refuses once that handoff has a report. Check that the scope matches your intent, that nothing essential was excluded, and that the passes fit the reviewer's context. Use --budget <tokens> to force a split of a scope that is too large for one pass.

For explicit paths instead of the change set, replace --changes with repeated --target <path|glob>; the engine still applies the hazard rules.

3. Send it to ChatGPT Pro

Default engine: the Pro engine reaches the web-only ChatGPT Pro tier through the pinned, guarded transport. Read The Pro engine before the first live run of a session.

node "$PRO_REVIEW_DIR"/scripts/pro-engine.mjs run \
  --manifest "<manifest dir>/manifest.json"        # add --pass N for later passes

Run that through the background command monitor with a deadline covering the 20-minute response allowance; a Pro answer usually takes 10-15 minutes.

Other engines (opt-in)

Planning with --client <name> selects a client engine instead of Pro. When the user asks for a different reviewer, or Pro is unavailable, pick one of these instead:

  • Pane client (default inside Herdr): the reviewer runs in its own visible pane with its full tool surface - best for long reviews, and you can watch or steer it.
  • Headless client: the same client in one-shot print mode - best outside Herdr or for scripted runs.
  • In-session subagent: OmO's own reviewer agent through the task tool - use it when Herdr is unavailable.

Send brief-pass<N>.md verbatim; it already carries the question, scope roles, digest, focus hints, exclusions, constraints, the report path, and the nonce. Compose a custom brief only when the template genuinely does not fit, and then follow Review brief and keep the output contract.

An explicit review invocation authorizes sending the scoped brief to the chosen engine. Installing the skill, or merely reading this file, does not request a live review. Stay inside the user's existing credentials: never add API keys, copy another client's auth, or switch a client's account. Keep the pane visible; never close a pane you did not create, and do not steal focus unless asked.

4. Harvest the artifact, never the echo

Wait for the report file the brief named - watch that path, or wait on the client's own settled state when Herdr tracks it. A marker echoed back from your own prompt is not an answer, and a fixed sleep is not a wait. Then run:

node "$PRO_REVIEW_DIR"/scripts/handoff.mjs verify \
  --report "<report path>" --manifest "<manifest path>" --format terminal

Exit 0 renders the summary (verdict, severity counts, findings with locations, checks, limits); exit 2 names exactly what the report is missing.

verify checks that a cooperating reviewer's report is complete and well-formed under a deliberately strict grammar (exact headings, one findings table, no raw HTML, fences only at column 0) and fails closed on anything outside it. It is not a defense against a reviewer that hides its own findings - such a reviewer could simply omit them - so always read the report artifact itself (step 5). Reject the report and ask for a corrected one instead of summarising an incomplete answer. If a client stalls, sits on an approval dialog, or loses its transport, recover the same pane or session rather than submitting a duplicate. Ask the user only for what a human must do: a login, an account choice, an approval prompt, or a decision to abandon the run.

5. Verify and report

Read the report artifact. Reproduce each proposed finding in the current code and run focused checks where needed. Separate confirmed defects, plausible risks, and unsupported claims; agreement between reviewers is not proof.

Return findings first, ordered by severity, with path:line, the failing condition, impact, and a minimal correction. State when there are no confirmed findings. Include unresolved questions, the reviewed scope, the checks actually run, the reviewer and engine used, the pane or output path, and the model identity the client itself reported. The filled report template lives at Report template; verify --format json emits the machine-readable form for scripted consumers.

Review-only requests end with the assessment; do not implement, commit, publish, or contact people unless the user separately asks for that work. For an existing authorized fix task, use verified findings within that task's scope.

See Design and evidence for what was verified on this machine and the difference between a client's self-reported model and independent attestation.

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