peer-review

name	peer-review
description	Run iterative cross-model peer review on substantive designs, code, plans, refactors, architecture, docs, or repo artifacts by delegating to the other local coding agent through peeragent. Use when the user asks for peer review, a second opinion, cross-review, feedback from Codex/Claude/Gemini/GLM, or when recent work is risky enough to deserve an independent review loop. Resolve the bundled wrapper from the plugin location; do not assume peeragent is on PATH.
allowed-tools	Bash
metadata	{"short-description":"Iterative cross-model peer review"}

Peer Review

A second pair of eyes from a different model, run as a loop. The other agent reviews; you weigh the feedback honestly; you refine the work; you ask again. Convergence is the goal — not consensus, not politeness, not a clean signoff no one earned.

When To Use

• You just finished a design, refactor, implementation, plan, or doc and want a real sanity check before declaring done.
• You suspect a blind spot — the kind of mistake only someone who didn't write it would catch.
• The user asked for peer review, a second opinion, cross-review, or feedback from "the other agent" in any phrasing.
• Proactively, after substantive work, when shipping unreviewed feels risky. You do not need explicit user permission to invoke this skill — proposing peer review is part of doing the work well.

Do not use this for trivial changes (a typo fix, a one-line rename). The loop is overhead; reserve it for work where the loop pays for itself.

The Other Agent

The peer reviewer is the agent you are not.

• If you are Claude Code, delegate review to Codex with <resolved-peeragent-bin> --agent codex ....
• If you are Codex, delegate review to Claude with <resolved-peeragent-bin> --agent claude ....
• Gemini is also available (--agent gemini) when the user asks for it or when the natural pair is unavailable.
• Z.AI GLM 5.2 through Pi is also available (--agent zai) when the user asks for GLM/Z.AI or when an additional model family is useful. This is the only Z.AI model peeragent surfaces.

The point of the alternate agent is different blind spots, not a more authoritative answer. Their misses are your catches and vice versa.

The Loop

Run at least 3 full review→refine passes. Continue past 3 only while substantive issues keep surfacing. Stop when a pass returns mostly nits (taste, minor wording, micro-style). Cap at 5 — if you are still in substantive disagreement after 5, the work needs a human, not more loops.

Each pass has five steps. Do all five every time.

1. Frame the review request

Tailor the framing to the type of work. Keep it open. Ask for "the good, the bad, and the ugly" — explicit permission for honest negatives. Do not tell the reviewer your conclusions; let them form their own.

Type of work	What to ask the reviewer for
Code / implementation	Correctness bugs, edge cases, security, reuse opportunities, simplifications.
Design / architecture	Coherence, missing concerns, scope errors, alternatives not considered, integration risks.
Plan / task breakdown	Completeness, sequencing, risk, hidden dependencies, unrealistic estimates.
Refactor	Whether the abstraction earns its weight, dead code, unintended behavior change.
Docs / writeup	Accuracy against the code, gaps, audience fit, lying-by-omission.

The prompt should orient on what kind of feedback you want and what the artifact is — not on the conclusions you want validated. Avoid leading questions ("don't you think X is good?"). The reviewer is in the same repo, so file paths work directly.

Include a no-recursion instruction in every review request. Tell the reviewer explicitly not to reach for peeragent's own peer or peer-review skills — and not to run the peeragent wrapper — to delegate the review back out to another local coding agent. That would loop host → reviewer → host and burn the review budget. The reviewer is the endpoint of this delegation; it should review directly. It may freely use its own harness's internal sub-agents for parallel or focused analysis; the prohibition is only on recursive peeragent calls. A short line in the prompt is enough, e.g. "Review this directly — do not call the peeragent peer/peer-review skills to hand it off again; use your own harness's sub-agents if you need help."

2. Delegate

A blocking call. Default model/effort is fine for most passes; bump effort only when the work is dense or the stakes are high.

Do not assume peeragent is on PATH. Resolve the bundled wrapper before the first call and use that path for every invocation:

• If PEERAGENT_BIN names an executable, use it.
• Otherwise resolve from this skill file: go two directories up from the skill directory, then use bin/peeragent.
• In a development checkout, the same wrapper is bin/peeragent.
• Use bare peeragent only if the bundled path cannot be found and command -v peeragent succeeds.

If a bare peeragent call fails with command not found, retry once with the bundled plugin path before reporting failure.

Run each review pass with the host harness's outside-sandbox command mode so the peer CLI inherits the developer machine's normal network, auth, hook, and process environment. In Codex, use the command tool's escalated/outside-sandbox execution mode for the wrapper invocation. This is separate from peeragent's --full-access flag: do not pass --full-access for review.

<resolved-peeragent-bin> --agent <other-agent> "Review the following <work type> and give
me the good, the bad, and the ugly. Focus on <task-specific concerns>.
Artifact: <paths or inline description>. Context: <what changed, what
success looks like>."

For a deeper review pass:

<resolved-peeragent-bin> --agent codex --effort xhigh "..."
<resolved-peeragent-bin> --agent claude --model opus --effort xhigh "..."
<resolved-peeragent-bin> --agent zai --effort xhigh "..."

Quickly test whether the Z.AI target is configured before relying on it in a review loop:

pi --list-models zai | grep -w 'glm-5.2'
pi --provider zai --model glm-5.2 --thinking high --no-session --no-tools -p 'Reply with OK.'
<resolved-peeragent-bin> --agent zai --text 'Reply with OK and do not edit files.'

If the Pi smoke test fails, configure Pi with ZAI_API_KEY or /login for the ZAI provider and retry. Peeragent does not expose other Z.AI models.

Claude Opus review passes, especially with --effort xhigh, may take 10 minutes or longer to finish. A slow or quiet Opus reply is not by itself evidence of a hung process; keep waiting unless the wrapper exits, reports failure, or there is concrete evidence the process is stuck.

For very large prompts, write to a file and use --prompt-file <path>. Never request --full-access for review — review shouldn't need it.

If the wrapper result includes metadata.agent_session, keep it for the current review loop. Use --resume <agent-session> on the next pass when you want the reviewer to evaluate whether its prior substantive concerns were addressed. Do not use --resume when the point is an independent second opinion or when the review scope materially changes.

3. Read the response honestly

For each point the reviewer raises, ask:

• Is it correct? Does the criticism hold up against the actual artifact, or did the reviewer misread? Verify before agreeing.
• Does it improve the work? Some valid observations don't justify a change — alternate-but-equal designs, taste preferences.
• What weight does it carry? Real bug > design risk > clarity issue > taste nit. Triage on weight, not volume.
• Does the reviewer have a blind spot here? Sometimes the reviewer misses context you have. Trust feedback that names a concrete problem; weigh skeptically feedback that's just "I'd do it differently".

You are not obligated to accept the reviewer's framing. You are obligated to consider it.

4. Apply the accepted changes

Make the real edits in the working tree. The work is what changes; the review is the signal. Nodding at feedback without applying it is the most common failure mode of this loop — guard against it.

If you reject a point, note why — to yourself, in a running summary you'll share with the user at the end.

5. Decide on the next pass

Look at what's left:

• Substantive issues outstanding → loop again.
• Reviewer caught new high-level issues this pass → keep looping; you haven't reached a stable design yet.
• Mostly nits and taste → after at least 3 passes, you're done.
• Reviewer is repeating themselves or contradicting their last pass → stop; that's noise.

Three is the minimum because pass 1 catches the obvious, pass 2 catches what you fixed badly, pass 3 confirms convergence.

How To Weigh Feedback

A healthy loop rejects roughly as many points as it accepts. Accepting everything is sycophancy; rejecting everything is stubbornness. Both fail.

Accept readily:

• Concrete bugs the reviewer can point at.
• Edge cases you genuinely missed.
• Naming, structure, or factoring issues you can confirm by re-reading.
• Reuse opportunities — duplicate logic that should be shared.
• Contracts or constraints the work violates.

Push back when:

• The reviewer asserts a "better" pattern without showing why the current one is worse.
• The suggestion would expand scope past what was asked.
• The suggestion contradicts an explicit user constraint or earlier decision.
• It's a taste preference dressed as a correctness claim.
• The reviewer is hallucinating about code or APIs that don't exist that way — verify before applying.

When you push back, do it in your own notes. Do not argue with the reviewer through another delegation — that wastes budget and doesn't change their position. Just don't apply the change.

Focus On The High-Level

The loop is for substantive concerns. Don't burn passes on nits.

• High-level (loop on these): correctness, design coherence, missing cases, integration risk, security, reuse, scope, contract violations.
• Nits (acknowledge and move on): variable naming preferences, whitespace, minor wording, single-line micro-optimizations, ordering of unrelated sections.

If a pass surfaces only nits, that's the signal you've converged. Apply the worthwhile ones, drop the rest, stop the loop.

Reporting Back To The User

After the loop ends, summarize:

• How many passes ran and why you stopped (converged on nits / hit cap / ran into noise).
• Substantive issues caught and fixed — the value the loop produced.
• Points raised and rejected, one line of reasoning each, so the user can override your judgment if they disagree.
• Final state of the work.

Keep it tight. The user doesn't need the full transcript of every pass — they need to know what got better, what you decided against, and where things landed.

Result Handling

The wrapper returns JSON by default. Per delegation:

• status: success — read the reviewer's response, run it through the honest-evaluation step, apply what you accept.
• status: blocked — note the blocker, evaluate the work yourself for that pass, or surface to the user if it's structural.
• status: failed — surface the failure; one retry is fine; don't loop on a broken wrapper.
  • If exit code 3 (or, in --text mode, a "no prebuilt binary for this platform" message), peeragent has no committed binary for the user's OS/arch. Prebuilt binaries cover linux/darwin on amd64/arm64. Tell the user: on those platforms, reinstall the plugin or download the matching archive from https://github.com/nklisch/peeragent/releases; on any other platform, install from source (requires Go) with go install github.com/nklisch/peeragent/cmd/peeragent@latest and set PEERAGENT_BIN. If the platform is misdetected, PEERAGENT_TARGET_OVERRIDE=<goos>-<goarch> selects a present binary. Do not retry in a loop.
• status: running (if --async was used) — record the job id and check back; usually peer review wants the blocking default.

Do not claim the reviewer signed off unless a pass actually returned without substantive findings.

Guardrails

• Apply what you accept. A loop that produces accepted feedback but no edits is a wasted loop.
• Don't loop on nothing. Pass returns only nits and you've done at least 3 — stop. Don't pad the count.
• Don't argue with the reviewer. Take the input, judge it, move on. The reviewer is a worker, not a debate partner.
• No recursive peeragent. The review request must tell the reviewer not to call peeragent's peer/peer-review skills (or the peeragent wrapper) back out to another agent. The reviewer's own internal harness sub-agents are fine; recursive peeragent delegation is not.
• You own the judgment. Don't ask the reviewer "is your last feedback right?" — they'll either confirm everything or contradict everything. The host weighs; the reviewer surfaces.
• Be honest in the summary. If you rejected most of the feedback, say so. Don't pretend the reviewer agreed with you.
• Trivial work doesn't need this skill. Use judgment — a one-line fix doesn't earn three peer-review passes.
• No --full-access for review. Reviews shouldn't need it.
• On exit code 3, tell the user to install a prebuilt binary (linux/darwin amd64/arm64) or build from source with Go; do not retry. No committed binary matches the host OS/arch — looping won't fix it.