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 manhvann/codexkit --skill docs-seekergit clone --depth 1 https://github.com/manhvann/codexkitWrote 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/manhvann/codexkit/docs-seeker)<a href="https://agentmods.dev/skills/manhvann/codexkit/docs-seeker"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/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/manhvann/codexkit/docs-seeker"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/docs-seeker.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 | $0.00037 | $0.00777 |
| Opus 5.5 | $0.00015 | $0.00311 |
| Sonnet 5.5 | $0.00007 | $0.00155 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
ck: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 1mo 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Discovery via Scripts
Overview
Script-first documentation discovery using llms.txt standard.
Execute scripts to handle entire workflow - no manual URL construction needed.
Primary Workflow
ALWAYS execute scripts in this order:
# 1. DETECT query type (topic-specific vs general)
node scripts/detect-topic.js "<user query>"
# 2. FETCH documentation using script output
node scripts/fetch-docs.js "<user query>"
# 3. ANALYZE results (if multiple URLs returned)
cat llms.txt | node scripts/analyze-llms-txt.js -
Scripts handle URL construction, fallback chains, and error handling automatically.
Scripts
detect-topic.js - Classify query type
- Identifies topic-specific vs general queries
- Extracts library name + topic keyword
- Returns JSON:
{topic, library, isTopicSpecific} - Zero-token execution
fetch-docs.js - Retrieve documentation
- Constructs context7.com URLs automatically
- Handles fallback: topic → general → error
- Outputs llms.txt content or error message
- Zero-token execution
analyze-llms-txt.js - Process llms.txt
- Categorizes URLs (critical/important/supplementary)
- Recommends agent distribution (1 agent, 3 agents, 7 agents, phased)
- Returns JSON with strategy
- Zero-token execution
Workflow References
Topic-Specific Search - Fastest path (10-15s)
General Library Search - Comprehensive coverage (30-60s)
Repository Analysis - Fallback strategy
References
context7-patterns.md - URL patterns, known repositories
errors.md - Error handling, fallback strategies
advanced.md - Edge cases, versioning, multi-language
Execution Principles
- Scripts first - Execute scripts instead of manual URL construction
- Zero-token overhead - Scripts run without context loading
- Automatic fallback - Scripts handle topic → general → error chains
- Progressive disclosure - Load workflows/references only when needed
- Agent distribution - Scripts recommend parallel agent strategy
What ships with it
16 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.
- .env.example 456 B
- package.json 630 B
- references/advanced.md 1.7 KB
- references/context7-patterns.md 1.5 KB
- references/errors.md 1.3 KB
- scripts/analyze-llms-txt.js 5.1 KB runs code
- scripts/detect-topic.js 4.4 KB runs code
- scripts/fetch-docs.js 4.9 KB runs code
- scripts/tests/run-tests.js 1.5 KB runs code
- scripts/tests/test-analyze-llms.js 3.7 KB runs code
- scripts/tests/test-detect-topic.js 3.9 KB runs code
- scripts/tests/test-fetch-docs.js 2.2 KB runs code
- scripts/utils/env-loader.js 2.4 KB runs code
- workflows/library-search.md 2.5 KB
- workflows/repo-analysis.md 2.2 KB
- workflows/topic-search.md 2.1 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.
- 1mo ago First seen · 99 lines · 37 tokens per session scan A 89a379cd00b5
ck:docs-seeker is a skill published in the GitHub repository manhvann/codexkit (89 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 777 once invoked, about $0.0001 per session on Opus 5.5. 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.
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