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 tamnguyendinh/Anvien --skill docs-seekergit clone --depth 1 https://github.com/tamnguyendinh/AnvienWrote 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/tamnguyendinh/anvien/docs-seeker)<a href="https://agentmods.dev/skills/tamnguyendinh/anvien/docs-seeker"><img src="https://agentmods.dev/badge/skills/tamnguyendinh/anvien/docs-seeker/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/tamnguyendinh/anvien/docs-seeker"><img src="https://agentmods.dev/badge/skills/tamnguyendinh/anvien/docs-seeker.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00015 | $0.01804 |
| Opus 5 | $0.00008 | $0.00902 |
| Sonnet 5 | $0.00003 | $0.00361 |
| Haiku 4.5 | $0.00002 | $0.00180 |
Grade A, and why
docs-seeker 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 11d 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.
This is a copy
89% identical to docs-seeker — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Discovery & Analysis
Overview
Intelligent discovery and analysis of technical documentation through multiple strategies:
- llms.txt-first: Search for standardized AI-friendly documentation
- Repository analysis: Use Repomix to analyze GitHub repositories
- Parallel exploration: Deploy multiple Explorer agents for comprehensive coverage
- Fallback research: Use Researcher agents when other methods unavailable
Core Workflow
Phase 1: Initial Discovery
-
Identify target
- Extract library/framework name from user request
- Note version requirements (default: latest)
- Clarify scope if ambiguous
- Identify if target is GitHub repository or website
-
Search for llms.txt (PRIORITIZE context7.com)
First: Try context7.com patterns
For GitHub repositories:
Pattern: https://context7.com/{org}/{repo}/llms.txt Examples: - https://github.com/imagick/imagick → https://context7.com/imagick/imagick/llms.txt - https://github.com/vercel/next.js → https://context7.com/vercel/next.js/llms.txt - https://github.com/better-auth/better-auth → https://context7.com/better-auth/better-auth/llms.txtFor websites:
Pattern: https://context7.com/websites/{normalized-domain-path}/llms.txt Examples: - https://docs.imgix.com/ → https://context7.com/websites/imgix/llms.txt - https://docs.byteplus.com/en/docs/ModelArk/ → https://context7.com/websites/byteplus_en_modelark/llms.txt - https://docs.haystack.deepset.ai/docs → https://context7.com/websites/haystack_deepset_ai/llms.txt - https://ffmpeg.org/doxygen/8.0/ → https://context7.com/websites/ffmpeg_doxygen_8_0/llms.txtTopic-specific searches (when user asks about specific feature):
Pattern: https://context7.com/{path}/llms.txt?topic={query} Examples: - https://context7.com/shadcn-ui/ui/llms.txt?topic=date - https://context7.com/shadcn-ui/ui/llms.txt?topic=button - https://context7.com/vercel/next.js/llms.txt?topic=cache - https://context7.com/websites/ffmpeg_doxygen_8_0/llms.txt?topic=compress
What ships with it
7 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.
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.
- 11d ago First seen · 208 lines · 15 tokens per session scan A 249ba4fadcf6
docs-seeker is a skill published in the GitHub repository tamnguyendinh/Anvien (9 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,804 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to docs-seeker, differing in 2 lines, and is treated as a copy.
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