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Review queue

Skill jamestexas/agents/skills/review-queue

Fan out isolated, one-per-PR code reviews across your review queue, then synthesize. Use when you have several peer PRs to review and want each in its own context + git worktree (no cross-PR pollution), with a single consolidated report at the end. Dispatches the pr-reviewer sub-agent (isolation worktree, read-only) per PR; pulls the queue from a review inbox (zen) or gh; optionally catches up via an observational memory layer if one is connected; posts nothing without explicit per-PR authorization.From its SKILL.md

Install
npx -y skills add jamestexas/agents --skill review-queue

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SKILL.md

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Review Queue — isolated per-PR reviews, fanned out and synthesized

The problem this solves: reviewing N peer PRs in one long session pollutes context — findings, file reads, and design intent from PR A bleed into PR B. This skill keeps each review in its own sub-agent + own git worktree, then consolidates. One command, N clean reviews, one report.

Model: the orchestrator (you, the main session) builds the worklist, dispatches one pr-reviewer sub-agent per PR, and synthesizes. The sub-agent carries the discipline (pr-review-kit) and isolation: worktree; the orchestrator never reviews a PR itself (that would re-pollute the main context).

Arguments

A list of PR numbers/URLs to review (e.g. 42088 42090 39311, or full chainguard-dev/mono#42090 refs). If empty, the skill builds the queue from your review inbox (Phase 0).


Phase 0 — Build the worklist + catch up

  1. Get the queue (first source that's available):
    • zen (if the zen MCP is connected): call zen_inbox — PRs awaiting you (configured authors + explicit review requests). This is the intended source.
    • gh fallback: gh search prs --review-requested=@me --state=open --json number,title,repository (and/or the repos you care about).
    • args: if the user passed PR refs, use those verbatim — skip discovery.
  2. Catch up via an observational memory layer (optional — only if your harness provides one, e.g. a memory/timeline MCP) — for each PR you're about to review, a quick timeline / text search to surface what changed and who reviewed since you last looked (especially if it's a re-review). This is the "stay current" layer — query it, don't carry it. Skip silently if no such source is connected.
  3. Confirm the list with the user before dispatching — show repo#number — title for each, note any that are drafts or already-approved, and let them prune. Don't fan out a dozen agents on an unconfirmed list.

Phase 1 — Fan out (one isolated reviewer per PR)

Dispatch one pr-reviewer sub-agent per confirmed PR, in parallel (independent work, no shared state). Each pr-reviewer already declares isolation: worktree + read-only tools, so it gets its own repo copy and clean context.

In each dispatch prompt, give the agent exactly what it needs (it can't ask you):

  • OWNER, REPO, N (PR number)
  • the canonical remote name for fetching (upstream on a fork checkout, else origin)
  • intent: review-only — return a structured summary, post nothing
  • any design-doc pointer you have (path/URL), so it doesn't have to hunt blind

Label each agent by PR (e.g. review:mono#42090) so progress is legible. Sub-agents can't spawn sub-agents — that's fine; the worker is flat by design.

Scale note: ~5 PRs fan out cleanly as parallel sub-agents. If you're ever past ~10–15, or you want the reviewers to adversarially cross-check each other before reporting, that's the Workflow tool's territory (codified orchestration, dozens of agents) — switch to it rather than hand-dispatching.


Phase 2 — Synthesize

Collect each sub-agent's structured summary (verdict + falsifiable matrix + blockers/nits/questions). Then produce one consolidated report:

  • Per-PR line: repo#N — VERDICT — one-line why (sortable: BLOCKED/CHANGES first, SHIP last).
  • Cross-PR themes: anything that recurs (same nit across PRs, a shared dependency two PRs both touch, a design question that spans them). This is the value the orchestrator adds over reading N separate reports.
  • What needs you: the short list of PRs where a human decision is required (a design call, an approve, a "reply to reviewer").

Verify before relaying: the sub-agents are competent but not infallible (misidentified targets, stale framing, phantom citations). For any blocker a sub-agent reports, spot-check its evidence command against the actual code before you present it as fact.


Phase 3 — Post (only on explicit, per-PR authorization)

Default posture: post nothing. The report is local until the user says, per PR, "post the review on #N" or "approve #N." Posting is the one side-effect that's visible to others; never batch-post or infer authorization. When authorized, follow pr-review-kit Phase 8 (body-only review, inline threads, or atomic batch) and verify it landed.


Hygiene

  • The pr-reviewer worktrees auto-clean when the agent makes no changes — and a review makes none — so they shouldn't accumulate. Still, git worktree list periodically and prune anything stale.
  • This skill orchestrates; the pr-reviewer agent and pr-review-kit skill carry the per-PR discipline. Keep the division: orchestrator builds the list + synthesizes; worker reviews one PR in isolation.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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