review

name	review
description	Reviews code changes or PRs across 11 perspectives, reporting via JSON structured output plus a human-readable report. Supports switching between quick and deep modes. Takes a PR number or working-tree diff as input.

review - Multi-perspective code review

Reviews the diff across 11 perspectives, classifies findings into Critical / Warning / Info, and reports them as JSON plus a human-readable report. It adopts the hybrid approach from ADR-0025 (quick: single agent / deep: parallel per-perspective subagents).

The deterministic logic (perspective selection, duplicate merging, separating cross-perspective conflicts, grouping, generating the human-readable report + embedding <!-- review-json:v1 -->) is handled by the bundled review.mjs engine (ADR-0028 R1, prior examples health-check.mjs / usage-check.mjs / skill-metrics.mjs). This SKILL.md is limited to the judgment layer — deciding perspectives from changed files (review.mjs select), producing findings per perspective (LLM judgment), and formatting + posting JSON + report via review.mjs render. The perspective definitions (perspectives/<axis>.md) and review-json Schema v1 are invariant.

Principles

• Only finding generation is LLM judgment: the LLM that reads the code decides "which perspective has what issue." The engine handles only the deterministic parts: selection (which perspectives to run) and aggregation/formatting (how to compile and present the findings).
• Internal representation is always JSON: all findings are held as JSON; PR comments and stdout are converted to human-readable format via the engine's renderer.
• The engine never overrides severity: severity determination follows the severity guide in the corresponding perspectives/<axis>.md. Do not arbitrarily raise or lower severity across perspectives.

Input

• When a PR number is given (#N or a bare number):
  • Fetch the diff with gh pr diff <N>, and the list of changed files with gh pr diff <N> --name-only
  • Fetch the PR description with gh pr view <N>
• When no arguments are given:
  • Fetch working-tree changes with git diff (list of changed files via git diff --name-only)
  • If there are no changes, fetch the branch diff with git diff main...HEAD (changed files via git diff --name-only main...HEAD)
  • If there are still no changes, report that there is nothing to review and exit

Options

• --axes=<axis,...>: Explicitly specify which perspectives to apply (overrides automatic selection; perspectives with default_enabled: false are only enabled when specified explicitly)
• --deep: Run in deep mode (launches subagents in parallel per perspective. Claude Code environment only; other adapters fall back to quick)

Perspectives (11 axes)

Perspective definitions use perspectives/<axis>.md as the SSOT. The frontmatter declares category / applies_when / skip_when / default_enabled / inspection items / severity guide / exit_criteria.drive_loop.

category	axis	default
required	correctness, security, conventions	Always applied
design	architecture, compatibility, maintainability	When applies_when matches
quality	testing, performance, observability	When applies_when matches
ux	usability, documentation	When applies_when matches

The perspective selection logic (category: required is always applied / default_enabled: false is applied only when specified explicitly via --axes / skip_when.diff_only_in is the highest-priority skip condition / applied on an OR match of applies_when) is implemented in review.mjs, which deterministically returns the applicable perspectives given the frontmatter as input. The only key skip_when supports is diff_only_in (undefined keys are ignored, for forward-compat).

Procedure

1. Determine applicable perspectives

Pass the list of changed files to review.mjs select and let it determine the applicable perspectives. The engine lives in the same directory as this SKILL.md (in Claude Code: ~/.claude/skills/review/review.mjs; for dogfooding: <repo>/.claude/skills/review/review.mjs):

# 変更ファイル一覧（1 行 1 パス）を stdin で渡す
git diff --name-only | node <この skill のディレクトリ>/review.mjs select [--axes=<a,b>]

The engine formats and prints an 適用観点 (n/11): block to stdout. Present that output as-is (do not reformat it). If you need a machine-readable perspective list, use --json ({ axesApplied, byCategory, unknownAxes, total }). Passing --axes overrides the selection and applies only those perspectives (including ones with default_enabled: false).

2. Generate findings (LLM judgment)

For each applicable perspective, review the diff according to the inspection items and severity guide in the corresponding perspectives/<axis>.md, and produce findings. Only this step is LLM judgment; it is not scripted.

Push each finding into the internal JSON in the following shape: { axis, severity ("critical"|"warning"|"info"), file, line, issue, why, suggestion }. Fundamental trade-offs (e.g. security ↔ DX, observability ↔ performance) are not recorded as findings; push them into the conflicts array ({ axes, file, line, description }) instead (without a severity, leaving the decision to the reader).

quick mode (default)

A single agent scans the applicable perspectives in order, adding findings to the internal JSON buffer per perspective.

deep mode (--deep)

Launch an independent worker (a unit of parallel execution) for each perspective; each worker reads the corresponding perspectives/<axis>.md and returns findings as JSON. On hosts that cannot run in parallel, evaluating each perspective independently in series produces an equivalent result. Input format for the worker:

axis: <axis-name>
mode: deep
context:
  base: <base-ref>
  head: <head-ref>
  pr_number: <N (optional)>

<diff>

The worker should be self-contained — reading the perspective MD and producing JSON output only (it does not call other skills). The mechanism for launching deep mode in parallel is host-dependent (Claude Code: see "Parallel launch in deep mode" in SKILL.claude-code.md). Adapters without a parallel execution mechanism fall back to quick. As described below, aggregation happens in the engine after the worker returns (do not add an aggregation agent inside the workflow).

3. Aggregation + report output

Assemble the generated findings (and conflicts) into JSON of the shape { mode, axes_applied, findings, conflicts }, and pass it to review.mjs render. The engine performs duplicate merging (merging identical file:line:issue entries into one and noting axes_merged), summary calculation (by_axis / total), grouping by perspective → severity → file, human-readable report generation, and embedding <!-- review-json:v1 -->:

# findings JSON を stdin で渡す（--input=<file> でも可）
printf '%s' "$FINDINGS_JSON" | node <この skill のディレクトリ>/review.mjs render

Present and post the engine's stdout (the human-readable report plus the trailing JSON embed) as-is. For a PR review, comment on the PR with gh pr comment <N> --body "<report>". Use --json to extract only the embedded Schema v1 JSON.

review-json Schema v1 (contract, invariant)

The JSON the engine embeds has the following shape (ADR-0025 Schema v1; drive re-reads this to evaluate the per-perspective exit_criteria.drive_loop):

{
  "version": "1",
  "mode": "quick",
  "axes_applied": ["security", "correctness", "..."],
  "findings": [
    {
      "axis": "security",
      "severity": "warning",
      "file": "src/x.ts",
      "line": 42,
      "issue": "...",
      "why": "...",
      "suggestion": "...",
      "axes_merged": ["security", "correctness"]
    }
  ],
  "conflicts": [
    { "axes": ["security", "usability"], "file": "src/y.ts", "line": 10, "description": "..." }
  ],
  "summary": {
    "by_axis": { "security": { "critical": 0, "warning": 1, "info": 0 } },
    "total": { "critical": 0, "warning": 1, "info": 3 }
  }
}

axes_merged and conflicts are optional fields (the engine adds them only when there is duplicate merging or a cross-perspective conflict).

Version migration policy

• version is a monotonically increasing integer (as a string). This ADR establishes "1"
• The reader side (e.g. drive) performs machine judgment only when version matches the current code's supported upper bound
• An unsupported version fails soft as unknown_review_version, ignoring the JSON and handling only the human-readable part
• Breaking changes bump version, and readers keep an implementation that can read at least down to N-1. When changing Schema v1, revise the engine (review.mjs), this SKILL.md, and drive's re-read logic together

Compatibility with past PR comments (resume)

Comments drive posted in the past may not have a JSON embed. The reader handles these as follows:

• A comment containing <!-- review-json:v1 ... --> → parse the JSON and do machine judgment
• A comment with no JSON → treated as a legacy comment and ignored as a trigger for a new review pass (past comments are not deleted)
• <!-- review-json:v<unknown> ... --> → ignored as unknown_review_version (fail-soft)

Notes

• When reporting even a single Critical, show clear grounds for adverse impact (a bug, vulnerability, etc.)
• Severity determination for a perspective follows the severity guide in the corresponding perspectives/<axis>.md. Do not arbitrarily raise or lower severity across perspectives
• deep mode consumes tokens proportional to (number of perspectives × parallelism). In drive's orchestration mode, it forcibly falls back to quick (cost management)
• Info is suggestion-only. drive's review loop does not treat Info as something to fix