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requesting-code-review
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Run a guarded commit-to-deploy workflow that verifies branch freshness, invokes commit and create-pr, waits for green CI, invokes approve-pr, monitors CD, and reports final deployment state. Use when the user asks to yolo-push, ship current changes, or execute the full PR-to-deployment flow.
Use when the user wants to analyze experiment results, inspect scores from a dataset run, check pass/fail rates, review per-item outputs, or deep-dive into experiment performance. Trigger phrases: "analyze results", "experiment scores", "how did the experiment perform", "show results", "inspect run", "experiment analysis".
Use when the user wants to compare two or more experiment runs, detect regressions, see score deltas between runs, or evaluate model performance differences. Trigger phrases include "compare runs", "compare experiments", "diff runs", "regression check", "which run is better", "model comparison", "A/B comparison".
This skill should be used when the user wants to configure a Langfuse dataset for remote experiment triggering from the UI, set up a webhook URL, update the default experiment payload, or enable the Custom Experiment feature. Trigger phrases include "configure remote experiment", "set webhook URL", "enable custom experiment", "set up experiment trigger", "configure dataset webhook".
This skill should be used when the user wants to create a new Langfuse dataset, set up a dataset for benchmarking, or create a dataset with input/output schema validation. Trigger phrases include "create dataset", "new dataset", "set up dataset", "add dataset".
| name | requesting-code-review |
| description | Use when completing tasks, implementing major features, or before merging to verify work meets requirements |
Dispatch a code reviewer subagent to catch issues before they cascade. The reviewer gets precisely crafted context for evaluation — never your session's history. This keeps the reviewer focused on the work product, not your thought process, and preserves your own context for continued work.
Core principle: Review early, review often.
Mandatory:
Optional but valuable:
1. Get git SHAs:
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main
HEAD_SHA=$(git rev-parse HEAD)
2. Dispatch code reviewer subagent:
Use Task tool with general-purpose type, fill template at code-reviewer.md
Placeholders:
{DESCRIPTION} - Brief summary of what you built{PLAN_OR_REQUIREMENTS} - What it should do{BASE_SHA} - Starting commit{HEAD_SHA} - Ending commit3. Act on feedback:
[Just completed Task 2: Add verification function]
You: Let me request code review before proceeding.
BASE_SHA=$(git log --oneline | grep "Task 1" | head -1 | awk '{print $1}')
HEAD_SHA=$(git rev-parse HEAD)
[Dispatch code reviewer subagent]
DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types
PLAN_OR_REQUIREMENTS: Task 2 from docs/dev-workflow/plans/deployment-plan.md
BASE_SHA: a7981ec
HEAD_SHA: 3df7661
[Subagent returns]:
Strengths: Clean architecture, real tests
Issues:
Important: Missing progress indicators
Minor: Magic number (100) for reporting interval
Assessment: Ready to proceed
You: [Fix progress indicators]
[Continue to Task 3]
Subagent-Driven Development:
Executing Plans:
Ad-Hoc Development:
Never:
If reviewer wrong:
See template at: requesting-code-review/code-reviewer.md