
requesting-code-review
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
- Installs
- 357
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/camacho/ai-skills --skill requesting-code-review- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads requesting-code-review automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
FAQ
What does the requesting-code-review skill do?
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
How do I install requesting-code-review?
Run npx skills add https://github.com/camacho/ai-skills --skill requesting-code-review in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/requesting-code-review/ (personal) or .claude/skills/requesting-code-review/ (project).
Which AI agents can use requesting-code-review?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is requesting-code-review safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains requesting-code-review?
It is published by camacho in camacho/ai-skills. It has 357 recorded installs.
More from camacho/ai-skills
archive
camacho/ai-skills
Fills Outcomes & Learnings in a plan file and renames it to .done.md.
bail
camacho/ai-skills
Reflects, updates GitHub Issue, closes PR if open, cleans up worktree/branch.
capture
camacho/ai-skills
Creates a draft GitHub Issue with triage label from natural language description.
plan-review
camacho/ai-skills
Auto-assembles review panel using deterministic rules, dispatches agents against plan file, collects verdicts.
orient
camacho/ai-skills
Fetches issue context, auto-detects task type, maps to branch prefix, presents brief.
reflect
camacho/ai-skills
Use after merging a branch or completing a task to consolidate learnings into memory layers, close out issues, and verify the phase gate.
Popular code quality & workflow skills
grill-me
mattpocock/skills
A relentless interview to sharpen a plan or design.
improve-codebase-architecture
mattpocock/skills
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
handoff
mattpocock/skills
Compact the current conversation into a handoff document for another agent to pick up.
domain-modeling
mattpocock/skills
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
codebase-design
mattpocock/skills
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.