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/flurdy/agent-skills/clean-codenpx skills add flurdy/agent-skills --skill clean-codegit clone --depth 1 https://github.com/flurdy/agent-skillsWhat 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 | $0.00025 | $0.00336 |
| Opus 5 | $0.00013 | $0.00168 |
| Sonnet 5 | $0.00005 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
clean-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.
What it actually says
Clean Code
Format, lint, and fix all warnings across the entire codebase — including test files and pre-existing issues.
Usage
/clean-code
Instructions
1. Run the project's clean-code target
Each project defines a make clean-code Makefile target with the appropriate tooling for its language/stack.
make clean-code
2. Fix remaining issues
If make clean-code fails or reports warnings/errors that couldn't be auto-fixed, investigate and fix them manually. Do NOT leave any warnings unresolved.
3. Verify clean state
Re-run the target to confirm it passes cleanly:
make clean-code
It must exit with zero warnings and zero errors.
Rules
- Do not skip or suppress warnings (e.g.
eslint-disable,#[allow(...)],@SuppressWarnings) unless there is a genuine false positive with a clear justification - Do not change the project's formatter or linter configuration
- If a fix changes behavior (not just style), flag it to the user before applying
- Test files are in scope — do not skip them
- Pre-existing issues must be fixed, not just new code
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 · 53 lines · 25 tokens per session scan A 24fbb5ccacd0
clean-code is a skill published in the GitHub repository flurdy/agent-skills (7 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 336 once invoked, about $0.0001 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.
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.
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…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
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.