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 KunanonJ/ai-skills-hub --skill context7-auto-researchgit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/context7-auto-research)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/context7-auto-research"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/context7-auto-research/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/kunanonj/ai-skills-hub/context7-auto-research"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/context7-auto-research.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 | $0.00048 | $0.00345 |
| Opus 5 | $0.00024 | $0.00172 |
| Sonnet 5 | $0.00010 | $0.00069 |
| Haiku 4.5 | $0.00005 | $0.00034 |
Grade A, and why
context7-auto-research 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- context7-auto-research — 100% identical, 0 lines differ
What it actually says
context7-auto-research
Overview
Automatically fetch latest library/framework documentation for Claude Code via Context7 API
When to Use
- When you need up-to-date documentation for libraries and frameworks
- When asking about React, Next.js, Prisma, or any other popular library
Installation
npx skills add -g BenedictKing/context7-auto-research
Step-by-Step Guide
- Install the skill using the command above
- Configure API key (optional, see GitHub repo for details)
- Use naturally in Claude Code conversations
Examples
See GitHub Repository for examples.
Best Practices
- Configure API keys via environment variables for higher rate limits
- Use the skill's auto-trigger feature for seamless integration
Troubleshooting
See the GitHub repository for troubleshooting guides.
Related Skills
- tavily-web, exa-search, firecrawl-scraper, codex-review
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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 · 45 lines · 48 tokens per session scan A ccea8ff8feb2
context7-auto-research is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 345 once invoked, about $0.0002 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.
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