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 pproenca/dot-skills --skill docs-searchgit clone --depth 1 https://github.com/pproenca/dot-skillsWrote 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/pproenca/dot-skills/docs-search)<a href="https://agentmods.dev/skills/pproenca/dot-skills/docs-search"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/docs-search/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/pproenca/dot-skills/docs-search"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/docs-search.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 | $0.00199 | $0.02098 |
| Opus 5 | $0.00100 | $0.01049 |
| Sonnet 5 | $0.00040 | $0.00420 |
| Haiku 4.5 | $0.00020 | $0.00210 |
Grade A, and why
docs-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 5d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docs Search — Navigation Methodology for Official Library Documentation
Methodology distillation of the generic moves an agent makes when reaching for a library's official documentation. Not a per-library skill — one skill plus a thin per-library record in the shared knowledge graph (/knowledge/libraries/), because 90% of the work is the same regardless of which library you're searching.
This is the navigation layer that sits next to library-reference-distillation. That skill is for authoring a full library-ref rule pack when you have time to extract idioms. This skill is for just looking something up when you don't — a lighter-weight, faster-to-author alternative whose unit of growth is a ~30-line topography record, not a full rule pack.
When to Apply
Use this skill when:
- An agent needs a specific answer from a library's official documentation and "search the docs" is the next move
- The user asks "where do I find X in
<library>docs?" or "did<library>change Y recently?" - The documentation appears to match the situation but production behavior diverges
- The agent is about to Google a library question and would benefit from going to the library's own site search, llms.txt, or changelog first
- A library has been used before and a topography record exists in
registry/— read it before navigating - A library has been used and no record exists yet — apply the methodology, then capture findings in
registry/<library>.mdso the next lookup is faster
This skill is not for:
- Authoring a library-reference rule pack — when you want to extract idioms and failure-gap rules into a distilled skill, use
library-reference-distillationinstead. Once a full library-ref skill exists for library X, the registry entry for X becomes redundant and should be cut. - General web search — if the question is not about a specific library's official docs (e.g., "what's the best practice for X across the ecosystem"), this is the wrong tool.
- Reading internal/proprietary docs — no llms.txt, no public changelog, no public issues. The methodology assumes public, versioned, OSS-style documentation.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- AGENTS.md 2.9 KB
- metadata.json 1.3 KB
- references/_sections.md 3.1 KB
- references/capture-registry-record.md 4.7 KB
- references/fall-known-issues.md 2.8 KB
- references/fall-samples-over-prose.md 3.1 KB
- references/src-bounded-knowledge-read.md 2.8 KB
- references/src-decision-tree.md 2.3 KB
- references/src-llms-txt-first.md 2.3 KB
- references/ver-changelog-first.md 2.4 KB
- references/ver-find-selector.md 2.5 KB
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.
- 5d ago First seen · 93 lines · 199 tokens per session scan A 5ce9560e107f
docs-search is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 199 tokens to every session and 2,098 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 2026-09-03.
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