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/cfircoo/claude-code-toolkit/file-searchnpx skills add cfircoo/claude-code-toolkit --skill file-searchgit clone --depth 1 https://github.com/cfircoo/claude-code-toolkitWrote 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/cfircoo/claude-code-toolkit/file-search)<a href="https://agentmods.dev/skills/cfircoo/claude-code-toolkit/file-search"><img src="https://agentmods.dev/badge/skills/cfircoo/claude-code-toolkit/file-search.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 | $0.00082 | $0.00489 |
| Opus 5 | $0.00041 | $0.00244 |
| Sonnet 5 | $0.00016 | $0.00098 |
| Haiku 4.5 | $0.00008 | $0.00049 |
Grade A, and why
file-search 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.
What it actually says
<search_modes> This skill handles all search types automatically based on input:
| Input Pattern | Search Mode | What Happens |
|---|---|---|
| File name or glob pattern | File search | Finds files by name/pattern across the project |
| Text string or regex | Content search | Greps file contents for matches |
| Function/class/type name | Definition search | Finds where something is defined + its signature |
| "usages of X" / "who calls X" | Usage search | Finds all imports and call sites |
| "imports of X" | Import search | Finds all files that import a module |
| Directory path or "structure" | Structure exploration | Maps directory layout and key files |
| "related to X" | Related files | Finds dependencies and dependents of a file |
The agent runs multiple search strategies in parallel and cross-references results for completeness. </search_modes>
<success_criteria>
- Returns file paths with line numbers for all matches
- Exhausts multiple search strategies before reporting "not found"
- Results are ordered by relevance
- No false positives — every result was verified by a tool call </success_criteria>
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 · 44 lines · 82 tokens per session scan A b7d4f0e93809
file-search is a skill published in the GitHub repository cfircoo/claude-code-toolkit (17 stars, last pushed 5mo ago), licensed MIT. It adds 82 tokens to every session and 489 once invoked, about $0.0004 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…