Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/pilotspace/pilot-space/review-codenpx skills add pilotspace/pilot-space --skill review-codegit clone --depth 1 https://github.com/pilotspace/pilot-spaceWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00031 | $0.01164 |
| Opus 5 | $0.00015 | $0.00582 |
| Sonnet 5 | $0.00006 | $0.00233 |
| Haiku 4.5 | $0.00003 | $0.00116 |
Grade A, and why
review-code scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Code Skill
Perform a production-grade code review on code blocks in the current note. Uses Opus for deep analysis, checking correctness, security vulnerabilities, performance bottlenecks, and adherence to project patterns. Writes structured feedback directly to the note.
Quick Start
Use this skill when:
- User requests a code review (
/review-code) - Agent detects code blocks that need quality checking
- User asks "review this" or "is this code correct?"
Example:
User: "Review this FastAPI endpoint I wrote"
AI reviews:
- Security: SQL injection risk in raw query? Missing RLS enforcement?
- Performance: N+1 query in loop? Missing eager loading?
- Correctness: Missing error handling? Wrong HTTP status codes?
- Style: Type hints? Pydantic v2 model? Conventional naming?
Workflow
-
Collect Code to Review
- Read all code blocks from the current note
- Use
search_note_contentto find referenced dependencies or patterns - Use
get_issueif issue context is in note headers
-
Analyze Code
- Security: OWASP Top 10, RLS enforcement, input validation, SQL injection, XSS
- Performance: N+1 queries, missing indexes, blocking I/O in async, connection pooling
- Correctness: Error handling completeness, type safety, edge cases, async/await usage
- Architecture: CQRS-lite compliance, repository pattern, separation of concerns, file size (<700 lines)
- Style: Type hints, docstrings on public APIs, naming conventions
-
Classify Findings
- CRITICAL: Security vulnerabilities, data loss risks, production crashes
- HIGH: Performance degradation, logic errors, missing error handling
- MEDIUM: Architecture violations, missing tests, style issues
- LOW: Minor improvements, optional optimizations, documentation gaps
-
Write Review to Note
- Use
write_to_noteto append a## Code Reviewsection - For each finding: severity badge + location + issue + suggested fix
- Include a summary scorecard
- Use
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 132 lines · 31 tokens per session scan A 46add90d0929
review-code is a skill published in the GitHub repository pilotspace/pilot-space (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,164 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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