gco-review
Code review using GitHub Copilot CLI. Use when: (1) User says 'gco review' or 'copilot review', (2) After implementation for quality check, (3) Child agents self-reviewing. Runs Copilot to review the diff, synthesizes findings. Falls back to Claude Code if Copilot unavailable.
Best use case
gco-review is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Code review using GitHub Copilot CLI. Use when: (1) User says 'gco review' or 'copilot review', (2) After implementation for quality check, (3) Child agents self-reviewing. Runs Copilot to review the diff, synthesizes findings. Falls back to Claude Code if Copilot unavailable.
Teams using gco-review should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gco-review/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gco-review Compares
| Feature / Agent | gco-review | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Code review using GitHub Copilot CLI. Use when: (1) User says 'gco review' or 'copilot review', (2) After implementation for quality check, (3) Child agents self-reviewing. Runs Copilot to review the diff, synthesizes findings. Falls back to Claude Code if Copilot unavailable.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# GCO Review
Code review via GitHub Copilot CLI, synthesized by Claude Code.
## Process
### Step 0: Pre-flight Rate Limit Check
Before doing anything, check if Copilot is currently in degraded mode:
```bash
RATE_CHECK=$(node $HOME/.claude/scripts/gco-rate-limit.js check 2>&1)
```
If the output starts with `degraded:`, **notify the user** that Copilot is in low-cost mode (auto-downgraded model) but **proceed with Copilot anyway** — it is still usable. Do NOT skip or fall back.
### Step 1: Determine Base Branch
```bash
BRANCH=$(git branch --show-current)
BASE=$(gh pr view --json baseRefName -q '.baseRefName' 2>/dev/null)
```
If no PR, use default branch:
```bash
BASE=$(git remote show origin | grep 'HEAD branch' | awk '{print $NF}')
```
### Step 2: Build Review Prompt
Generate the diff and build a review prompt:
```bash
DIFF=$(git diff "$BASE"...HEAD)
```
Construct the prompt:
```
Review the following code changes (diff against $BASE branch).
Focus on:
1. Bugs, logic errors, and potential runtime failures
2. Security vulnerabilities (injection, XSS, auth issues)
3. Performance problems
4. Missing error handling at system boundaries
5. Breaking changes or regressions
For each finding, provide:
- File and approximate location
- Severity (high/medium/low)
- What the issue is and why it matters
- Suggested fix
Be concise. If the code looks good, say so briefly — don't invent problems.
Diff:
<the diff content>
```
### Step 3: Run Copilot
```bash
LOGDIR=$(node $HOME/.claude/scripts/get-logdir.js)
mkdir -p "$LOGDIR"
DATETIME=$(date +%Y%m%d_%H%M%S)
bash $HOME/.claude/skills/gco/scripts/gco-run.sh \
"<prompt>" \
"$LOGDIR/${DATETIME}-gco-review.md" \
"$LOGDIR/${DATETIME}-gco-review-stderr.log"
```
Run as a **background Bash task** with 15-minute timeout.
### Step 4: Collect Results
After Copilot completes (or times out):
1. Read the output file (`$LOGDIR/${DATETIME}-gco-review.md`)
2. If empty or missing, check stderr log for errors (a 402 no-quota error means Copilot Premium is exhausted — treat it as a failure)
3. If Copilot failed or timed out, jump to **Fallback**
### Step 5: Fallback
If Copilot timed out, produced **no usable output**, hit **no-quota (402)**, or is **not installed**:
- **Notify the user** about the fallback
- Spawn **2 `code-reviewer` subagents** in parallel (like /light-review) to review the diff against `$BASE`
- Continue as if `/light-review` was invoked
### Step 6: Synthesize and Report
1. Read output and organize findings
2. Categorize by priority (high / medium / low)
3. Present a clear summary
4. Include log file paths for reference
### Step 7: Apply Fixes
- **High priority**: Implement automatically
- **Medium priority**: Implement if clearly safe, otherwise ask
- **Low priority**: Ask user
### Step 8: Commit Changes
If fixes were applied, commit with a descriptive message.
## Important Notes
- Copilot cannot modify files — all writes done by Claude Code
- NEVER use `~` in paths — use `$HOME`
- Output files: `$LOGDIR/${DATETIME}-gco-review.md` (timestamped)Related Skills
review-loop
Iterative code review loop running /deep-review multiple times, fixing issues each round. Each round: review (safe fixes applied inline by the reviewer) → big-but-decidable findings are fix-planned, implemented, and merged back via an in-session /big-plan -m -a chain → next round reviews the improved code. Only findings needing a genuine human decision are deferred into GitHub issues (-nori to suppress). Use when: (1) User says 'review-loop', 'review loop', or 'review repeat', (2) User wants continuous review+fix cycles, (3) User wants autonomous review → fix → improve passes before finalizing code, (4) User says 'review 5 rounds' or similar.
light-review
Lightweight code review. Dispatches to OpenAI Codex CLI (/codex-review) by default, or to Claude / Copilot depending on flags. Use when: (1) Quick review of a small change, (2) Child agents self-reviewing before reporting to manager, (3) User says 'light review' or 'quick review', (4) Review is needed but /deep-review is overkill. Always operates in PR/diff mode.
deep-review
Deep code quality review focused on structure, refactoring, and best practices. Use when: (1) User says 'review', 'deep review', or 'code review', (2) After implementation when a quality check is needed, (3) Before marking a PR as ready. Default backend is /codex-review. Opt into Claude reviewers with -haiku|-so|-op (auto-detects PR vs full-project mode). Supports -co|-gco external backends. Default team-fix mode (-t) delegates fixes to /x-wt-teams --no-review --stay; pass -nt/--no-team for inline fixes. Unfixed findings become agent-found GitHub issues by default (-nori to suppress).
codex-review
Code review using OpenAI Codex CLI (codex exec review). PREFERRED over /light-review for code review. Use when: (1) User says 'review', 'code review', or 'codex review', (2) After implementation when quality check is needed, (3) Child agents self-reviewing. Runs multiple codex review instances in parallel. Falls back to Claude Code if codex unresponsive.
zudoesa-articlify
Convert conversation context into an esa article via the zudoesa-writer subagent. ONLY invoke when the user explicitly asks — NEVER proactively propose. Triggers: 'write esa article', 'esa記事', 'esaに書いて', 'articlify for esa', or /zudoesa-articlify. Gathers context, creates a writing brief, delegates to the writer subagent.
zudoesa-apply-voice
Apply Takazudo's esa writing voice and vocabulary rules to text. Use when: (1) User wants to write/rewrite text in Takazudo's esa style, (2) User says 'apply voice', 'esa voice', 'esa文体で', 'esa風に書いて', '文体を適用', (3) User provides text to transform to esa style. Reads writing-style.md and vocabulary-rule.md from takazudo-esa-writing repo and applies the rules.
zudocg-articlify
Convert conversation context into a CodeGrid article via the zudocg-writer subagent. ONLY invoke when the user explicitly asks — NEVER proactively propose. Triggers: 'write codegrid article', 'CodeGrid記事', 'codegridに書いて', 'articlify for codegrid', or /zudocg-articlify. Gathers context, creates a writing brief, delegates to the writer subagent.
zudocg-apply-voice
Apply Takazudo's CodeGrid writing voice and vocabulary rules to text. Use when: (1) User wants to write/rewrite text in Takazudo's CodeGrid style, (2) User says 'apply voice', 'codegrid voice', 'codegrid文体で', 'codegrid風に書いて', '文体を適用', (3) User provides text to transform to CodeGrid style. Reads writing-style.md and vocabulary-rule.md from takazudo-codegrid-writing repo and applies the rules.
zpaper-articlify
Convert conversation context into a zpaper blog article via the zpaper-writer subagent. ONLY invoke when the user explicitly asks — NEVER proactively propose. Triggers: 'write zpaper article', 'zpaper記事', 'zpaperに書いて', 'articlify for zpaper', or /zpaper-articlify. Gathers context, creates a writing brief, delegates to the writer subagent.
zpaper-apply-voice
Apply Takazudo's zpaper blog writing voice and vocabulary rules to text. Use when: (1) User wants to write/rewrite text in Takazudo's zpaper style, (2) User says 'apply voice', 'zpaper voice', 'zpaper文体で', 'zpaper風に書いて', 'ブログ文体を適用', (3) User provides text to transform to zpaper style. Reads writing-style.md and vocabulary-rule.md from the zpaper repo and applies the rules.
xlsx
Spreadsheet creation, editing, and analysis. Use when working with .xlsx, .xlsm, .csv, .tsv files for: (1) Creating spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modifying existing spreadsheets while preserving formulas, (4) Data analysis and visualization, (5) Recalculating formulas.
x
Facade for development workflows. Routes on two axes: plan-first vs implement-now (escalates to /big-plan -a when the request needs research / decomposition / has unclear scope — the appended -a makes the plan chain into implementation in-session), then single vs multi on the ready-to-build fast paths (/x-as-pr single-topic, /x-wt-teams multi-topic parallel). Use when: (1) User says '/x' followed by dev instructions, (2) User wants to start development without choosing the workflow skill, (3) User says 'dev', 'implement', or 'build' with a task. Default option: -v (verify-ui). Review-loop (-l) is opt-in — without -l the downstream skill runs a single /deep-review pass. Forwards -a (autonomy/auto-chain) and -m (merge at the end + cleanup + CI watch) through every route; auto-fix of raised findings (-f) and issue-raising (-ri) are downstream defaults, with -nf/--no-fix and -nori/--no-raise-issues as the forwarded opt-outs. -a and -m are orthogonal — full hands-off end-to-end is -a -m.