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/tessro/fab/reviewnpx skills add tessro/fab --skill reviewgit clone --depth 1 https://github.com/tessro/fabWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tessro/fab/review)<a href="https://agentmods.dev/skills/tessro/fab/review"><img src="https://agentmods.dev/badge/skills/tessro/fab/review.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00034 | $0.00607 |
| Opus 5 | $0.00017 | $0.00303 |
| Sonnet 5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
review 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 4d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Perform a thorough code review of your changes before marking your task as complete.
When to Use
Run /review after you have finished implementing a feature, bug fix, or any code changes, but BEFORE running fab issue close or fab agent done.
How to Review
Use the Task tool to spawn a sub-agent for code review. This provides a fresh perspective without the context of how the code was written, leading to more objective reviews.
Step 1: Run the Sub-Agent Review
Use the Task tool with subagent_type: "general-purpose" and a prompt like:
Review all code changes (committed and uncommitted) between main and the current worktree. Run `git diff main` to see all changes.
Check each of these areas:
1. **Correctness**: Does the code solve the problem? Are there logic errors or unhandled edge cases?
2. **Completeness**: Is the implementation fully complete? Any TODOs left behind?
3. **Testing**: Are there tests for new functionality? Do existing tests pass?
4. **Code Quality**: Is the code readable and well-organized? Does it follow project conventions?
5. **Documentation**: Are public APIs documented? Do complex algorithms have comments?
6. **Security**: Any potential vulnerabilities (injection, XSS, etc.)? Is user input validated?
7. **Performance**: Any obvious performance issues (N+1 queries, unnecessary loops)?
Run the test suite and any linters configured for the project.
Report:
- Issues found (with file paths and line numbers)
- Suggestions for improvement
- Confidence level that the implementation is complete and correct
Step 2: Address Feedback
CRITICAL: You MUST address all issues found during review before proceeding. Do not skip, defer, or ignore feedback. The review exists to catch problems - ignoring it defeats the purpose.
After the sub-agent completes its review:
- Carefully read through ALL issues and suggestions reported
- Fix every problem identified - no exceptions
- If the sub-agent raised concerns, address each one explicitly
- If significant changes were made, run
/reviewagain to verify fixes
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.
- 4d ago First seen · 66 lines · 34 tokens per session scan A 6fe593195e3c
review is a skill published in the GitHub repository tessro/fab (23 stars, last pushed 7mo ago), licensed MIT. It adds 34 tokens to every session and 607 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…