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 skills add anymouschina/TapCanvas --skill code-reviewgit clone --depth 1 https://github.com/anymouschina/TapCanvasWrote 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/anymouschina/tapcanvas/code-review)<a href="https://agentmods.dev/skills/anymouschina/tapcanvas/code-review"><img src="https://agentmods.dev/badge/skills/anymouschina/tapcanvas/code-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anymouschina/tapcanvas/code-review"><img src="https://agentmods.dev/badge/skills/anymouschina/tapcanvas/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00038 | $0.01107 |
| Opus 5.5 | $0.00015 | $0.00443 |
| Sonnet 5.5 | $0.00008 | $0.00221 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
code-review scanned grade A with 1 finding 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 1mo 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
os.system(f"ls {user_input}") How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Skill
You now have expertise in conducting comprehensive code reviews. Follow this structured approach:
Review Checklist
1. Security (Critical)
Check for:
- Injection vulnerabilities: SQL, command, XSS, template injection
- Authentication issues: Hardcoded credentials, weak auth
- Authorization flaws: Missing access controls, IDOR
- Data exposure: Sensitive data in logs, error messages
- Cryptography: Weak algorithms, improper key management
- Dependencies: Known vulnerabilities (check with
npm audit,pip-audit)
# Quick security scans
npm audit # Node.js
pip-audit # Python
cargo audit # Rust
grep -r "password\|secret\|api_key" --include="*.py" --include="*.js"
2. Correctness
Check for:
- Logic errors: Off-by-one, null handling, edge cases
- Race conditions: Concurrent access without synchronization
- Resource leaks: Unclosed files, connections, memory
- Error handling: Swallowed exceptions, missing error paths
- Type safety: Implicit conversions, any types
3. Performance
Check for:
- N+1 queries: Database calls in loops
- Memory issues: Large allocations, retained references
- Blocking operations: Sync I/O in async code
- Inefficient algorithms: O(n^2) when O(n) possible
- Missing caching: Repeated expensive computations
4. Maintainability
Check for:
- Naming: Clear, consistent, descriptive
- Complexity: Functions > 50 lines, deep nesting > 3 levels
- Duplication: Copy-pasted code blocks
- Dead code: Unused imports, unreachable branches
- Comments: Outdated, redundant, or missing where needed
5. Testing
Check for:
- Coverage: Critical paths tested
- Edge cases: Null, empty, boundary values
- Mocking: External dependencies isolated
- Assertions: Meaningful, specific checks
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.
- 1mo ago First seen · 158 lines · 38 tokens per session scan A 0db1126646e8
code-review is a skill published in the GitHub repository anymouschina/TapCanvas (678 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 1,107 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
md-audit
Read-only code quality audit — scan the current working directory for common issues (bugs, dead code, security hotspots, missing error handling) and return a prioritised findings report. No files are edited. Use when asked to "audit the code", "quick audit", "find issues", "code scan", or "what's wrong with this…
write-pr
Reference standards for writing pull request titles and descriptions in the tldraw repository, plus the pre-flight comment sweep over the diff. Use as supporting guidance when another skill or workflow needs PR content standards, not as the user-facing create/update PR workflow.
code-review
Perform comprehensive code review with best practices.
refactor
Suggest refactoring improvements for code quality.
pr-walkthrough
Create a narrated video walkthrough of a pull request with code slides and audio narration. Use when asked to create a PR walkthrough, PR video, or walkthrough video.
shepherd-pr
Keep an eye on this PR. Review and resolve pull request comments and fix build failures autonomously. Use when asked to review PR feedback, address reviewer comments, fix CI failures, resolve PR threads, or handle PR maintenance tasks like "review PR comments", "fix the build", "address PR feedback", "clean up PR", or…