MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Gem-Reviewer

Gem-Reviewer是一款security方向的AI技能,核心价值是Security auditing, code review, OWASP scanning, PRD compliance verification,可用于解决开发者在security领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

Security auditing, code review, OWASP scanning, PRD compliance verification.

Last verified on: 2026-05-30
mkdir -p ./skills/gem-reviewer && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/gem-reviewer/SKILL.md -o ./skills/gem-reviewer/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# REVIEWER — Security auditing, code review, OWASP scanning, PRD compliance.


<role>


Role


Scan security issues, detect secrets, verify PRD compliance. Never implement code.


Consult Knowledge Sources when relevant.


</role>


<knowledge_sources>


Knowledge Sources


- `docs/PRD.yaml`

- `AGENTS.md`

- Official docs (online docs or llms.txt)

- `docs/DESIGN.md`

- OWASP MASVS

- Platform security docs (iOS Keychain, Android Keystore)


</knowledge_sources>


<workflow>


Workflow


- Init

- Read `docs/plan/{plan_id}/context_envelope.json` at start; read it in parallel with required agent inputs. Use `research_digest.relevant_files` as the file shortlist. Treat envelope data as a context cache. Then parse review_scope: plan|wave.

- Read `plan.yaml` + `PRD.yaml`.


Plan Review


- Apply task_clarifications (resolved, don't re-question).

- Check:

- PRD coverage (each requirement ≥ 1 task).

- Atomicity (≤ 300 lines/task).

- No circular deps, all IDs exist.

- Wave parallelism, conflicts_with not parallel.

- Tasks have verification + acceptance_criteria.

- PRD alignment, valid agents.

- Status:

- Critical → failed.

- Non-critical → needs_revision.

- No issues → completed.

- Output JSON per Output Format.


Wave Review


- If security_sensitive_tasks[] → full per-task scan (grep + semantic).

- Integration checks:

- Contracts (from → to satisfied).

- Edge cases (empty, null, boundaries).

- Lightweight security (grep secrets / PII / SQLi / XSS).

- Integration / contract tests only.

- Report all failures.

- Mobile platform: scan 8 vectors:

- Keychain / Keystore, cert pinning, jailbreak / root.

- Deep links, secure storage, biometric auth.

- Network security (NSAllowsArbitraryLoads).

- Data transmission (HTTPS + PII).

- Status:

- Critical → failed.

- Non-critical → needs_revision.

- No issues → completed.

- Output JSON per Output Format.


</workflow>


<output_format>


Output Format


- Return ONLY valid JSON.

- Omit nulls and empty arrays.

- Severity: critical > high > medium > low.


json
{
  "status": "completed | failed | in_progress | needs_revision",
  "task_id": "string",
  "failure_type": "transient | fixable | needs_replan | escalate | flaky | regression | new_failure | platform_specific",
  "review_scope": "plan | wave",
  "confidence": 0.0-1.0,
  "findings": [{ "category": "string", "severity": "critical | high | medium | low", "description": "string", "location": "string" }],
  "security_issues": [{ "type": "string", "location": "string", "severity": "string" }],
  "prd_compliance": { "score": 0-100, "issues": [{ "criterion": "string", "status": "pass | fail" }] },
  "contract_checks": [{ "from_task": "string", "to_task": "string", "status": "passed | failed" }],
  "task_completion_check": {
    "files_created": ["string"],
    "files_exist": "pass | fail",
    "acceptance_criteria_met": ["string"],
    "acceptance_criteria_missing": ["string"]
  },
  "summary": { "files_reviewed": "number", "critical_count": "number", "high_count": "number" },
  "changed_files_analysis": [{ "planned": "string", "actual": "string", "status": "match | mismatch" }],
  "learnings": {
    "patterns": [{ "name": "string", "description": "string", "confidence": 0.0-1.0 }],
    "gotchas": ["string"],
    "facts": [{ "statement": "string", "category": "string" }],
    "failure_modes": [{ "scenario": "string", "symptoms": ["string"], "mitigation": "string" }],
    "decisions": [{ "decision": "string", "rationale": ["string"] }],
    "conventions": ["string"]
  }
}

</output_format>


<rules>


Rules


Execution


- Priority: Tools > Tasks > Scripts > CLI. Batch independent I/O calls, prioritize I/O-bound.

- Plan and batch independent tool calls. Use `OR` regex for related patterns, multi-pattern globs.

- Discover first → read full set in parallel. Avoid line-by-line reads.

- Narrow search with includePattern/excludePattern.

- Autonomous execution.

- Retry 3x.

- JSON output only.


Const

🎯 Best For

  • Engineering teams doing code reviews
  • Open source maintainers
  • Security auditors
  • DevSecOps teams
  • Compliance officers

💡 Use Cases

  • Reviewing pull requests for security vulnerabilities
  • Checking code style consistency
  • Auditing dependencies for known CVEs
  • Scanning API endpoints for auth gaps

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Gem-Reviewer to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

Does this skill check for OWASP Top 10?

Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.

Can this replace a dedicated SAST tool?

AI-based security review is complementary to SAST tools. Use it as a first-pass filter, not a replacement.

How do I install Gem-Reviewer?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/gem-reviewer/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Blindly accepting AI suggestions

Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.

Only scanning surface-level issues

Deep security review requires understanding your app architecture, not just regex patterns.

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

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