| name | pr-multi-agent-review |
| description | Orchestrate a panel of local AI coding CLIs (claude, codex, agy, opencode, copilot, agency copilot) to independently review the Pull Request currently checked out, then collate their findings into one consensus-first markdown report plus a visual HTML dashboard. Use this whenever the user wants a "multi-agent", "panel", "multi-model", or "second opinion" review of the current branch/PR, asks to "review this PR with several agents / models", wants reviews "collated" or "cross-checked" across tools, or wants the review to also cover tests, a manual testing plan, documentation updates, and unresolved GitHub review threads. Nothing is posted to GitHub — the output is local files. Do NOT use for reviewing a pasted snippet, a remote PR that is not checked out, or when the user wants a single reviewer (use pr-review-dashboard for a solo visual review). |
| allowed-tools | Bash, Read, Write, Skill |
PR Multi-Agent Review
Run several AI coding CLIs as an independent review panel over the currently checked-out PR, then synthesize their reviews into one report. The value over a single reviewer is triangulation: a finding three tools independently flag is almost certainly real; a finding only one raises is either a sharp catch or a false positive — and the report should make that distinction visible so the user knows where to spend attention.
Nothing is posted to GitHub. Every artifact is a local file in a temp directory.
Requirements. git and at least one reviewer CLI are mandatory. gh + jq are needed for PR description and unresolved-thread context — without either, the skill degrades gracefully (diff + commits only) and says so. A timeout/gtimeout binary is used if present; otherwise a built-in bash watchdog enforces the per-reviewer timeout. The scripts avoid GNU-only flags (readlink -f, mktemp --suffix) so they run on stock macOS as well as Linux.
Trust boundary (read this). Two distinct exposures, because the panel feeds untrusted PR content — body, commit messages, third-party review comments, the diff — into the reviewer CLIs:
- Prompt-injection → tool execution. Four tools (
copilot, opencode, agency, agy) run without a hard read-only sandbox — the first three with --allow-all-tools, agy with its auto-approving --sandbox — so a malicious PR could attempt to drive them. Run this skill on PRs you trust, or isolate those tools (throwaway worktree, network off) when reviewing fork/contributor branches.
- Data egress. Every reviewer streams the PR content to its model provider (Anthropic, OpenAI, GitHub, Google, …). If an external contributor pasted a secret into a PR body or comment, running the panel sends it to those third parties. Don't review PRs containing sensitive data you can't share with the reviewers' backends.
Step 5 covers the specifics.
The orchestrator (you) never reviews the code yourself. Your job is to gather context, dispatch the panel, and collate. If you inject your own opinions as if they were a reviewer's, you destroy the signal of how many independent tools agreed. You may reconcile and judge their findings during collation, but the findings must originate from the panel.
Workflow at a glance
- Preflight — confirm a feature branch is checked out; find the base branch.
- Gather context — diff, commits, PR description, changed files, unresolved GitHub threads → write to a temp context dir.
- Build the dashboard — invoke the
pr-review-dashboard skill for the visual artifact.
- Pick the panel — detect which reviewer CLIs are installed; apply any model overrides the user asked for.
- Dispatch — run every reviewer in parallel, headless and read-only, each writing its own review file.
- Collate — synthesize all reviews (consensus-first) into
FINAL-REPORT.md.
- Deliver — print the paths and a three-line summary.
Use a TodoList to track these — step 5 fans out into one task per reviewer and it's easy to lose one.
Step 1: Preflight
The whole skill is meaningless off a feature branch, so fail fast. Run the bundled helper, which detects the default branch and verifies you're not on it or in detached HEAD.
Resolve the skill directory portably (BSD readlink has no -f), then source the preflight output rather than eval-ing it — the helper emits printf %q-quoted assignments, so a branch name containing shell metacharacters (', ;, $(...) — all legal in git refs) can't execute code in your shell:
SKILL_LINK=~/.claude/skills/pr-multi-agent-review/SKILL.md
SKILL_TARGET="$(readlink "$SKILL_LINK" 2>/dev/null || echo "$SKILL_LINK")"
SKILL_DIR="$(cd "$(dirname "$SKILL_TARGET")" && pwd -P)"
PREFLIGHT="$(mktemp)"
if "$SKILL_DIR/scripts/gather_pr_context.sh" --preflight-only > "$PREFLIGHT"; then
source "$PREFLIGHT"
rm -f "$PREFLIGHT"
else
rm -f "$PREFLIGHT"
fi
If the helper exits non-zero it has already printed the reason (on $DEFAULT_BRANCH, detached HEAD, no commits ahead of base). Relay that to the user and stop — do not try to review nothing.
Step 2: Gather PR context
Create a temp workspace and populate it. One helper does all of it so every reviewer reads identical inputs. PR_REVIEW_SKIP_FETCH=1 reuses the refs the preflight already fetched, avoiding a redundant second git fetch:
WORKDIR="$(mktemp -d)/pr-review" && mkdir -p "$WORKDIR"
PR_REVIEW_SKIP_FETCH=1 "$SKILL_DIR/scripts/gather_pr_context.sh" "$WORKDIR"
ls -1 "$WORKDIR/context"
After it runs, $WORKDIR/context/ contains:
diff.patch — the full git diff $BASE...HEAD (three-dot: what GitHub shows)commits.txt — git log $BASE..HEAD with bodieschanged-files.txt — name-status listpr-description.md — title + body + labels from gh pr view, or a note that no PR exists yetunresolved-threads.md — every unresolved review thread (human reviewers and the GitHub Copilot bot), with file/line, author, and the comment bodymeta.env — OWNER, REPO, PR_NUMBER, BASE, CURRENT_BRANCH, PR_URL for your own use
The PR description is author intent, not ground truth — the diff is ground truth. The unresolved threads matter because a good panel review should tell the user whether issues already raised on GitHub are addressed by the latest code, not re-litigate them blind. Both get fed to every reviewer and folded into the final report.
If gh is missing or the branch has no PR, the helper still produces the diff/commit/file context and writes a clear "no GitHub PR found" note into the description and threads files — the review proceeds on the diff alone.
Step 3: Build the visual dashboard
Invoke the pr-review-dashboard skill to produce the interactive HTML. It understands the same checked-out PR and gives the user a visual way to load the change into their head while the panel runs:
Use the Skill tool: pr-review-dashboard
When it finishes, note the HTML path it produced — you'll link it from the final report and mention it in delivery. Kick this off (or let it run) alongside step 5 if you can; it's independent of the panel.
Step 4: Pick the review panel
Only run tools that are actually installed — invoking a missing binary wastes a turn and clutters the report. Detect what's available:
"$SKILL_DIR/scripts/detect_reviewers.sh"
It prints one line per candidate: available <label> <tool> or missing <tool>. The candidate roster is claude, codex, agy (Google Antigravity CLI), opencode, copilot, and agency (agency copilot). Build your panel from the available lines and tell the user which tools were skipped and why ("agy not in PATH — skipping").
Models and reasoning effort: pre-selected by default
By default, pass no model flag and no effort flag — each tool uses whatever model and reasoning level it's configured with. This respects the user's existing setup and is what they want unless they say otherwise.
Override only when the user explicitly names models or a reasoning effort. The interesting case is running the same tool more than once with different models — e.g. "run agency copilot with a Claude model and again with a GPT model." Model-capable tools accept --model/-m; the panel just gets two entries for that tool, each with a distinct label so their reviews don't collide. Each panel entry is a label | tool | model | effort tuple (model and effort default to empty):
| User asks for | Panel entries (label | tool | model | effort) |
|---|
| default (no models named) | claude|claude||, codex|codex||, … one per available tool |
| "agency copilot with sonnet and with gpt-5" | agency-sonnet|agency|claude-sonnet-4.5|, agency-gpt5|agency|gpt-5| |
| "codex on gpt-5-codex" | codex|codex|gpt-5-codex| |
| "Copilot with extra-high reasoning" | copilot|copilot||xhigh |
Reasoning effort is per-tool and the valid values differ — pick one the chosen tool accepts: copilot/agency use --effort (none, low, medium, high, xhigh, max; "extra high" = xhigh); codex uses the model_reasoning_effort config (minimal, low, medium, high); opencode uses --variant (provider-specific, e.g. minimal, low, high, max). claude and agy have no reasoning-effort flag, so an effort request for them is ignored with a note and the reviewer still runs.
The label is yours to choose — make it readable and unique (it becomes the review filename and the section header). See references/reviewer-cli-matrix.md for exactly how each tool is invoked and which support --model / --effort.
Step 5: Dispatch the panel
Every reviewer gets the same instructions + context so differences in output reflect the models, not the prompt. Diff delivery is now uniform — every tool gets the full diff on stdin — but run_reviewer.sh still owns it, because it appends the diff and handles the per-tool invocation. You build a diff-less prompt with build_prompt.sh --no-diff and hand the diff to run_reviewer.sh separately:
"$SKILL_DIR/scripts/build_prompt.sh" --no-diff \
"$WORKDIR/context" "$SKILL_DIR/references/review-prompt.md" \
> "$WORKDIR/review-prompt.nodiff.txt"
Why embed the context in the prompt rather than point reviewers at the files? The panel CLIs disagree sharply on filesystem sandboxing — opencode hard-rejects any path outside its working directory (so it would read nothing from a /tmp context dir), others need per-tool --add-dir flags. Embedding sidesteps all of it: every reviewer gets byte-identical inputs with zero file-permission friction, and can still read the repo it's running in for surrounding context.
run_reviewer.sh takes the diff via --diff-file and embeds it into each reviewer's prompt, then delivers the whole thing the same way for every tool — that uniformity is the reason large PRs don't break:
- Every reviewer (
claude, codex, agy, opencode, copilot, agency) gets the diff-less prompt plus the full diff concatenated onto stdin, via a file redirect, which has no size limit. (Five of the six CLIs were verified to read the full prompt from stdin — a 450 KiB tail-token probe round-tripped intact — so the older "argv-only, omit the diff on overflow" path is gone. agy is wired the same way by analogy to its gemini-cli lineage but is not yet live-verified — smoke-test it.)
copilot and agency additionally run with --context long_context, which selects the larger context-window tier so a big PR fits without changing the model you've configured. If a model still overflows (no long tier, or the diff exceeds even the long window), run_reviewer.sh detects it and writes an errored status telling you to re-run that label with --model <larger-context model> — it never silently swaps your model.
Read references/review-prompt.md yourself once so you know what you're asking the panel to produce — it directs each reviewer to cover correctness, security, performance, error handling, concurrency, API/compat, test quality, human + agentic documentation, to end with a manual testing plan, all cited to file:line, and to wrap the whole review between ===PR-REVIEW-BEGIN===/===PR-REVIEW-END=== sentinels.
Then launch one background task per panel entry — they're independent and slow (each is a full agent run), so parallelism is the difference between one minute and ten. For each entry run:
"$SKILL_DIR/scripts/run_reviewer.sh" \
--label "<label>" --tool "<tool>" --model "<model-or-empty>" \
--effort "<effort-or-empty>" \
--prompt-file "$WORKDIR/review-prompt.nodiff.txt" \
--diff-file "$WORKDIR/context/diff.patch" \
--output-file "$WORKDIR/reviews/<label>.md" --timeout 900
Launch each as a background Bash task (run_in_background: true) so they run concurrently and you get notified as each finishes. run_reviewer.sh owns every per-tool quirk — headless flag, read-only mode, model flag, stdin delivery, the timeout (with a pure-bash watchdog fallback when neither timeout nor gtimeout is installed), capturing stdout/stderr, and extracting the review from between the sentinels so the TUI progress chatter that copilot/agency print to stdout doesn't pollute the review. It writes the cleaned review to <label>.md, the unfiltered capture to <label>.md.raw, and a one-line status to <label>.md.status.
Read-only and the untrusted-input boundary
Read-only is enforced where the tool supports it (codex --sandbox read-only, claude --permission-mode plan). copilot, opencode, agency, and agy have no hard read-only switch — copilot/opencode/agency run with --allow-all-tools, and agy runs with --sandbox (terminal-restricted but auto-approving), so only the prompt asks them not to write. That is a real exposure: the prompt embeds untrusted PR content (body, commit messages, third-party review-thread comments, the diff), and a crafted "ignore previous instructions…" payload could drive a fully tool-enabled agent. The post-run git status check catches tracked-file writes only — not reads, network calls, or untracked files.
Mitigate, don't pretend it's airtight:
- Only run this skill on PRs you trust unless you've isolated the no-sandbox tools. Tell the user this plainly when the PR is from a fork or an unknown contributor.
- For untrusted branches, prefer reviewing inside a throwaway git worktree and/or with networking disabled for the
copilot/opencode/agency runs.
- Before dispatching, capture
git status --porcelain as a baseline; after the panel finishes, diff it again. If a reviewer wrote a stray file, note it; don't blindly revert (you might clobber the user's uncommitted work).
As each task completes, glance at its .status and the head of its review file. ok = a clean sentinel-wrapped review. ok-empty = the tool ran but emitted no sentinels (it likely refused or rambled); the salvaged/raw output is kept so you can judge it. errored = it crashed, timed out (a stub .md is still written so the member stays visible to collation), or auth failed — and now also covers context overflow: a status of "prompt exceeded the model's context window; re-run this label with --model <larger-context model>" means even --context long_context couldn't hold the PR, so relay that suggestion to the user rather than treating it as a generic crash. A missing reviewer is information, not something to hide or silently retry more than once.
Step 6: Collate into the final report
Once every task has finished (or errored), read all of $WORKDIR/reviews/*.md, plus unresolved-threads.md and pr-description.md. Write $WORKDIR/FINAL-REPORT.md using the structure below.
The organizing principle is consensus first: lead with what multiple reviewers independently agree on, because agreement across independent models is the strongest signal in the whole exercise. Preserve disagreement honestly — if two tools call something a bug and one calls it correct, the user needs to see the conflict, not an averaged-away mush. Keep each reviewer's raw output linked in an appendix so nothing is lost.
# Multi-Agent PR Review: <PR title or branch>
<one-paragraph orientation: what the PR does, how big, how many reviewers ran, the single most important takeaway>
**PR:** <PR_URL or "no GitHub PR — local branch <CURRENT_BRANCH>">
**Base:** <BASE> · **Panel:** <label list> · **Skipped:** <tools not in PATH>
**Dashboard:** <path to the pr-review-dashboard HTML>
## Consensus findings
<!-- Raised by 2+ reviewers. Highest confidence. Each: severity, file:line, the issue,
and which panel members flagged it. Order by severity then by agreement count. -->
| Severity | Finding | Location | Flagged by |
|---|---|---|---|
## Single-reviewer findings worth surfacing
<!-- Raised by exactly one reviewer but credible. These are the sharp catches OR the false
positives — label your read of which, and say why. -->
## Disagreements
<!-- Where reviewers contradict each other. State both positions and your reconciliation,
or "needs author judgment" if you genuinely can't adjudicate from the diff. -->
## Testing assessment
<!-- Synthesized across the panel: does the PR test the new behavior? What's untested?
Are the tests meaningful or box-ticking? -->
## Documentation assessment
<!-- Two distinct questions, answered separately:
- Human docs: README / docs/ / user-facing .md updated where the change warrants it?
- Agentic docs: CLAUDE.md / AGENTS.md / .github/copilot-instructions.md / GEMINI.md /
.cursor rules updated if the change affects how agents should work in this repo?
"Not needed" is a valid answer — say so explicitly rather than omitting. -->
## Manual testing plan
<!-- Concrete, ordered steps a human can run to validate this PR by hand: setup, the actions
to take, and the expected result for each. Deduped and merged from the panel's plans. -->
## Status of unresolved GitHub threads
<!-- For each unresolved thread from context: does the latest diff appear to address it?
(addressed / partially / not addressed / can't tell). This is why we fetched them. -->
## Prioritized action list
<!-- The "if you do nothing else, do these" list, severity-ordered. -->
## Appendix: raw reviews
<!-- One link per panel member to its file under reviews/, plus any that errored. -->
Severity vocabulary, used consistently: Critical (blocks merge / data loss / security hole) · High (a reviewer would block on it) · Medium (should fix, not blocking) · Low (minor) · Info (noteworthy, no action). When reviewers use different scales, normalize to this one so the table is comparable.
Step 7: Deliver
Print the three artifact paths plainly so the user can open them:
FINAL-REPORT.md — the collated review- the dashboard HTML — visual understanding
reviews/ — each panel member's raw output
Then give a three-line spoken summary: one line on what the PR does, one on the most important consensus finding, one on the biggest open question or disagreement. Point the user to the report for the rest. Do not post anything to GitHub — this skill only ever reads the PR and writes local files.
Reference files
references/review-prompt.md — the shared prompt template handed to every reviewer. Read it before dispatching so you know what the panel was asked to do.references/reviewer-cli-matrix.md — exact headless/read-only invocation and model-flag support for each CLI. Consult when a reviewer behaves oddly or when adding a new tool.
