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/ahernandez-developer/claude-crap/adoptnpx skills add ahernandez-developer/claude-crap --skill adoptgit clone --depth 1 https://github.com/ahernandez-developer/claude-crapWrote 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/ahernandez-developer/claude-crap/adopt)<a href="https://agentmods.dev/skills/ahernandez-developer/claude-crap/adopt"><img src="https://agentmods.dev/badge/skills/ahernandez-developer/claude-crap/adopt.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 | $0.00195 | $0.01580 |
| Opus 5 | $0.00097 | $0.00790 |
| Sonnet 5 | $0.00039 | $0.00316 |
| Haiku 4.5 | $0.00019 | $0.00158 |
Grade A, and why
adopt 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Help a team adopt claude-crap gradually
Walk the user through picking the right initial strictness mode for claude-crap on their workspace, then hand them the exact .claude-crap.json to commit. The whole interaction should take under two minutes — it is an onboarding assistant, not a full quality audit.
Interview
Ask the user these three questions, one at a time. Wait for each answer before moving to the next so the user is not overwhelmed.
- "How much existing test coverage does your workspace have — would you call it green (80%+, most modules are tested), patchy (some well-tested, some bare), or near-zero?"
- "Have you run any SAST or quality scanners on the workspace recently — Semgrep, ESLint with security rules, Bandit, Stryker, anything like that? Roughly how many
error-level findings would a fresh scan produce: zero, a handful (say 1–5), or more than that?" - "Does the team want claude-crap to hard-block task closures from day one, or would you rather see the quality verdict for a week first and decide to enforce it later?"
Recommendation logic
Pick the strictness using this table. The principle is simple: if the project would immediately red-light under strict mode, don't start there — the team will just disable the plugin. Start at the loosest mode that still surfaces the findings, and tighten over time.
| Test coverage | Existing error findings | Wants hard block from day one? | Recommend |
|---|---|---|---|
| Green | 0 | Yes | strict |
| Green | 0 | No / unsure | warn |
| Green | 1–5 | Either | warn |
| Patchy | 0 | Either | warn |
| Patchy | 1–5 | Either | advisory |
| Patchy | 6+ | Either | advisory |
| Near-zero | Any | Any | advisory |
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 · 75 lines · 195 tokens per session scan A 829bc80b3196
adopt is a skill published in the GitHub repository ahernandez-developer/claude-crap (8 stars, last pushed 4mo ago), licensed MIT. It adds 195 tokens to every session and 1,580 once invoked, about $0.0010 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.
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…