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Adaptive code review that routes to haiku/sonnet/opus based on diff complexity signals. Use instead of requesting-code-review for cost-efficient reviews.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/2233admin/adaptive-review --skill adaptive-reviewコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SOC 職業分類に基づく
SKILL.md を表示中
| name | adaptive-review |
| description | Adaptive code review that routes to haiku/sonnet/opus based on diff complexity signals. Use instead of requesting-code-review for cost-efficient reviews. |
Review code changes with model depth proportional to change complexity. No wasted opus tokens on trivial diffs.
Run these commands to gather diff signals:
# Get diff stats (against HEAD~1 or origin/main, whichever makes sense)
BASE=$(git merge-base HEAD origin/main 2>/dev/null || echo "HEAD~1")
git diff --stat $BASE..HEAD
git diff --numstat $BASE..HEAD
Extract:
Then scan for high-risk patterns — only in code files (exclude .md/.txt/.json/.yaml from grep):
git diff $BASE..HEAD -- '*.ts' '*.js' '*.py' '*.go' '*.rs' '*.java' '*.c' '*.cpp' '*.rb' '*.sh' | grep -ciE '(password|secret|token|auth|session|cookie|sql|inject|exec\(|eval\(|lock|mutex|semaphore|atomic|concurrent|unsafe)'
| Condition | Depth | Model |
|---|---|---|
| lines_changed < 50 AND files_changed <= 1 AND risk_hits == 0 | fast | haiku |
| lines_changed < 200 AND dirs_changed <= 1 AND risk_hits <= 2 | medium | sonnet |
| Everything else (>200 lines OR dirs_changed >= 2 OR risk_hits > 2) | deep | opus |
Announce the routing decision:
Review depth: [fast|medium|deep] (N lines, N files, N dirs, N risk hits)
Spawn agent with model: "haiku", subagent_type of your code-review agent:
Prompt focus: formatting, naming conventions, obvious bugs, unused imports. Skip architecture analysis. Keep it under 30 seconds.
Spawn agent with model: "sonnet", subagent_type of your code-review agent:
Standard code review: correctness, error handling, test coverage, code quality.
Spawn agent with model: "opus", subagent_type of your code-review agent:
Full review: architecture, security, performance, cross-module impact. If language-specific reviewers exist (python-reviewer, go-reviewer, database-reviewer), spawn them in parallel.
Present results with depth label so the user knows what level of review was applied:
## Adaptive Review: [FAST|MEDIUM|DEEP]
Signals: {lines} lines, {files} files, {dirs} dirs, {risk_hits} risk hits
[reviewer output]
If fast review finds anything concerning, suggest upgrading: "Fast review flagged potential issues. Run /adaptive-review --deep for thorough analysis."
User can force depth:
/adaptive-review --fast — force fast regardless of signals/adaptive-review --deep — force deep regardless of signals/adaptive-review --medium — force medium