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 MerkyorLynn/Lynn --skill rag-assistantgit clone --depth 1 https://github.com/MerkyorLynn/LynnWrote 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/merkyorlynn/lynn/rag-assistant)<a href="https://agentmods.dev/skills/merkyorlynn/lynn/rag-assistant"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/rag-assistant/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/merkyorlynn/lynn/rag-assistant"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/rag-assistant.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 | $0.00041 | $0.00308 |
| Opus 5 | $0.00020 | $0.00154 |
| Sonnet 5 | $0.00008 | $0.00062 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
rag-assistant 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 9d 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.
What it actually says
RAG Assistant 知识库助手
当用户问题可能涉及已加入知识库的文档时，按以下流程执行：
检索流程
- 理解问题：提取核心实体和查询意图
- 调用 knowledge_query：传入精简后的查询词，top_k 取 5-7
- 评估相关性：若返回片段与用户问题无关，说明知识库未覆盖，改用 web_search
- 组织答案：
- 每个事实必须标注来源文件（如
📄 来源: xxx.pdf） - 区分「知识库内容」和「通用知识」
- 若多份文档观点冲突，需指出并总结
- 每个事实必须标注来源文件（如
适用场景
- "我之前上传的那份报告里怎么说？"
- "对比文档 A 和文档 B 的结论"
- "根据我的资料，总结一下 XX 的趋势"
不适用场景
- 通用知识查询（直接用 web_search）
- 未索引文档的内容（提示用户先使用 knowledge_index）
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.
- 9d ago First seen · 29 lines · 41 tokens per session scan A cc74a8792b41
rag-assistant is a skill published in the GitHub repository MerkyorLynn/Lynn (42 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 308 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 2026-08-30.
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