
Requesting Code Review
- 357 installs
- 1 repo stars
- Updated May 26, 2026
- camacho/ai-skills
requesting-code-review is a Claude Code skill that prepares and submits code changes for agent or human review with scoped context and diffs for developers who need pre-merge quality verification.
About
requesting-code-review is a Claude Code skill from camacho/ai-skills that dispatches a code-reviewer agent with precisely crafted evaluation context instead of dumping full session history. It mandates review after subagent-driven tasks, major feature completion, and before merge to main so defects surface early. The skill packages diffs, test evidence, and focused questions so reviewers judge the work product—not the author's reasoning trail—preserving author context for continued coding. Developers reach for requesting-code-review when they want structured pre-merge gates in agent-assisted workflows.
- PR description and context templates
- Diff scope and change summarization
- Test and verification evidence
- Targeted reviewer questions
- Risk and rollback callouts
Requesting Code Review by the numbers
- 357 all-time installs (skills.sh)
- Ranked #269 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 357 |
|---|---|
| repo stars | ★ 1 |
| Last updated | May 26, 2026 |
| Repository | camacho/ai-skills ↗ |
How do you request an AI code review before merge?
Prepare and submit code changes for review with clear context, diffs, test evidence, and focused questions so reviewers can approve efficiently.
Who is it for?
Developers using agent-assisted workflows who want mandatory pre-merge review with isolated reviewer context after major features or subagent tasks.
Skip if: Greenfield prototyping with no code to diff, security-only audits without implementation changes, or teams that forbid automated review agents on their branches.
When should I use this skill?
A developer completes a major feature, finishes a subagent-driven task, or is about to merge and needs a structured code review dispatch.
What you get
Reviewer-ready context package with diffs, test evidence, focused questions, and an agent review report before merge.
- reviewer context package
- agent review findings
Files
Requesting Code Review
Dispatch a code-reviewer agent (or invoke /review if available) 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.
When to Request Review
Mandatory:
- After each task in subagent-driven development
- After completing major feature
- Before merge to main
Optional but valuable:
- When stuck (fresh perspective)
- Before refactoring (baseline check)
- After fixing complex bug
How to Request
1. Get git SHAs:
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main
HEAD_SHA=$(git rev-parse HEAD)2. Dispatch code-reviewer:
Dispatch a code-reviewer agent (or invoke /review if available) with the following context:
Placeholders to fill in:
{WHAT_WAS_IMPLEMENTED}- What you just built{PLAN_OR_REQUIREMENTS}- What it should do{BASE_SHA}- Starting commit{HEAD_SHA}- Ending commit{DESCRIPTION}- Brief summary
Review request template:
Please review the code changes between {BASE_SHA} and {HEAD_SHA}.
What was implemented: {WHAT_WAS_IMPLEMENTED}
Requirements / plan reference: {PLAN_OR_REQUIREMENTS}
Summary: {DESCRIPTION}
Focus on:
- Correctness vs. requirements
- Missing edge cases or error handling
- Test quality (are tests testing real behavior or mocks?)
- Security concerns
- Code clarity and maintainability
Use project's code review template if one exists (e.g., check for a REVIEW_TEMPLATE or similar in the project docs).3. Act on feedback:
- Fix Critical issues immediately
- Fix Important issues before proceeding
- Note Minor issues for later
- Push back if reviewer is wrong (with reasoning)
Example
[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 agent or invoke /review]
WHAT_WAS_IMPLEMENTED: Verification and repair functions for conversation index
PLAN_OR_REQUIREMENTS: Task 2 from ai-workspace/plans/deployment-plan.md
BASE_SHA: a7981ec
HEAD_SHA: 3df7661
DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types
[Reviewer 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]Integration with Workflows
Subagent-Driven Development:
- Review after EACH task
- Catch issues before they compound
- Fix before moving to next task
Inline Plan Execution:
- Review after each batch (3 tasks)
- Get feedback, apply, continue
Ad-Hoc Development:
- Review before merge
- Review when stuck
Red Flags
Never:
- Skip review because "it's simple"
- Ignore Critical issues
- Proceed with unfixed Important issues
- Argue with valid technical feedback
If reviewer wrong:
- Push back with technical reasoning
- Show code/tests that prove it works
- Request clarification
Related skills
How it compares
Use requesting-code-review when you need a structured agent dispatch with mandatory pre-merge triggers; use receiving-code-review when integrating feedback from an existing review.
FAQ
When is requesting-code-review mandatory?
requesting-code-review is mandatory after each subagent-driven development task, after completing a major feature, and before merging to main. The skill enforces early, frequent review so issues do not cascade downstream.
What context does requesting-code-review send to reviewers?
requesting-code-review sends precisely crafted evaluation context—diffs, test evidence, and focused questions—without the author's full session history. Reviewers evaluate the work product while the author keeps context for continued coding.