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/hamchowderr/braynee/docs-lookupnpx skills add hamchowderr/braynee --skill docs-lookupgit clone --depth 1 https://github.com/hamchowderr/brayneeWhat 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 | $0.00102 | $0.00863 |
| Opus 5 | $0.00051 | $0.00432 |
| Sonnet 5 | $0.00020 | $0.00173 |
| Haiku 4.5 | $0.00010 | $0.00086 |
Grade A, and why
docs-lookup 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.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
docs-lookup — clean docs on demand (llms.txt model)
Put a tool/SDK's docs where you can search them, without crawling the whole site.
Backed by ${CLAUDE_PLUGIN_ROOT}/scripts/mirror-llms-docs.mjs (Node built-in
fetch, zero deps, cross-platform).
The model — three layers, in order
- Index (always). A site's root
llms.txtis a curated link-map of its docs. Save it once as a navigable index note. This is the map, not the territory. - On-demand (default). When you actually need a page, fetch that one page's clean-markdown route right then. Don't pre-copy pages you don't use.
- Curated copies (sparingly). Copy verbatim only the handful of pages you
reference constantly (kept minimal, stamped
verbatim-copy, re-fetched to refresh).
Never mirror a whole site. Verbatim-or-link: copied pages are stored as-is and never hand-edited — re-run the fetch to refresh.
Run it
# 1. Save the root llms.txt as an index note in <target-dir>
node "${CLAUDE_PLUGIN_ROOT}/scripts/mirror-llms-docs.mjs" index <domain> <target-dir> ["Note Name"]
# e.g.
node "${CLAUDE_PLUGIN_ROOT}/scripts/mirror-llms-docs.mjs" index mastra.ai "<target-dir>" "Mastra Docs Index"
# 2. Copy specific clean pages verbatim into <target-dir>
node "${CLAUDE_PLUGIN_ROOT}/scripts/mirror-llms-docs.mjs" pages <target-dir> <clean-page-url> [<clean-page-url> ...]
<target-dir> is whatever folder should hold the docs (a vault docs folder, a
repo docs/ dir, a scratch dir). The script hardcodes no paths.
Per-site clean-page routes
| Site | Root index | Clean per-page route |
|---|---|---|
| Mastra | https://mastra.ai/llms.txt |
append .md (e.g. .../docs/agents/overview.md) — the /llms.txt per-page route was retired 2026-07-04 |
| Docker | https://docs.docker.com/llms.txt |
append .md (e.g. .../engine/install.md) |
| other | https://<domain>/llms.txt |
check the site's own retrieval guidance for its clean-page route |
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 · 65 lines · 102 tokens per session scan A 9a6c8924af2b
docs-lookup is a skill published in the GitHub repository hamchowderr/braynee (2 stars, last pushed 6d ago), licensed MIT. It adds 102 tokens to every session and 863 once invoked, about $0.0005 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…