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 luna-jmy/thinkdokit-skills --skill rag-skillgit clone --depth 1 https://github.com/luna-jmy/thinkdokit-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/luna-jmy/thinkdokit-skills/rag-skill)<a href="https://agentmods.dev/skills/luna-jmy/thinkdokit-skills/rag-skill"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/rag-skill/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/luna-jmy/thinkdokit-skills/rag-skill"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/rag-skill.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 | $0.00103 | $0.04438 |
| Opus 5 | $0.00051 | $0.02219 |
| Sonnet 5 | $0.00021 | $0.00888 |
| Haiku 4.5 | $0.00010 | $0.00444 |
Grade A, and why
知识库 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.
How it starts
The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
本地知识库检索 Skill(kb-retriever)
知识库目录说明
- 知识库存放在一个根目录下,包含多种文件类型(如
.md/.txt、.pdf、.xlsx等),通常按类型或业务用途拆分为多级子目录。 - 采用分层目录索引文件:
- 根目录有一个
index.md,说明主要的「领域目录」及其用途。 - 每个领域目录下可以有自己的
index.md,说明该目录下有哪些子目录/文件,以及各自用途。 - 更深一层的子目录也可以继续有
index.md,形成多级索引树。 - 除
index.md外,moc.md(Map of Content)也是索引目录文件,检索时应一并查找。
- 根目录有一个
- 知识库根目录约定:
- 默认认为知识库位于当前项目根目录下的
知识库/目录。 - 如果用户在对话中明确指定了其他路径(例如”我的知识库在 /data/kb”或”用 ./docs 这个目录作为知识库”),则以用户指定的路径作为根目录。
- 当默认路径
知识库/不存在或访问失败时,应向用户确认实际的知识库根目录位置,而不是随意猜测。
- 默认认为知识库位于当前项目根目录下的
- 单个业务文件可能很大:
- 不要直接用 Read 读取整文件
- 对 PDF、Excel 使用对应 Skill 进行结构化处理后,再结合 grep/局部读取做精细检索
定位 知识库 根目录
- 根目录优先听用户:如果用户给了路径(如
./docs、./knowledge-personal),直接用用户提供的路径。 - 默认根目录:否则约定根目录为当前项目下的
知识库/。- 使用 shell 显式检查目录是否存在:优先使用
test -d 知识库,或退而求其次使用ls -d 知识库。 - 注意:禁止使用
Glob “知识库” in .这类模式来判断目录是否存在,Glob只返回文件路径,不返回目录本身,空结果并不能区分”目录不存在”和”目录存在但为空”。
- 使用 shell 显式检查目录是否存在:优先使用
- 只有在根目录已通过
test -d等方式确认存在时,才使用 Glob 在该目录下检索内容,并把目录作为path,例如:- 索引文件:
pattern="**/index.md",path="知识库" - 所有 Markdown:
pattern="**/*.md",path="知识库"
- 索引文件:
- 如果默认
知识库/不存在(test -d失败):不要猜测其他目录,明确告诉用户未找到默认根目录,并让用户指定实际知识库路径。
关键原则:先学习,再处理
遇到 PDF 或 Excel 文件时的强制检查清单:
- ✅ 已读取对应的 references 文档学习处理方法
- ✅ 已理解推荐的工具和命令
- ✅ 已将文件处理(提取/转换)完成
- ⏭️ 现在可以开始检索
禁止行为:
- ❌ 在未读取 pdf_reading.md 的情况下直接尝试处理 PDF
- ❌ 在未读取 excel_reading.md 的情况下直接尝试处理 Excel
- ❌ 跳过文件处理步骤,直接对原始 PDF/Excel 进行检索
总体流程
-
理解用户需求
- 读用户问题,提取:
- 主题/领域关键词(如“销售报表”“系统架构”“接口文档”)
- 时间或范围限定(如“2023 年 Q1”“最近版本”)
- 需要的输出类型(解释、摘要、具体字段数值等)
- 确定知识库根目录:
- 优先检查用户是否在问题中指定了知识库路径。
- 否则使用默认根目录
知识库/。 - 若默认根目录不存在或目录结构异常,应向用户询问确认,而不是自行假设。
- 读用户问题,提取:
-
分层查看目录索引
index.md- 使用一个「当前工作目录」的概念:
- 默认从用户指定的知识库根目录开始;如果用户未指定,则使用当前目录。
- 在当前工作目录下,如果存在
index.md或moc.md:- 使用 Read 读取该文件的前若干行(例如 limit=300),必要时分段继续读取。
- 目标:
- 了解当前目录下有哪些子目录和文件
- 理解每个子目录/文件的用途说明
- 基于用户问题,挑选最相关的若干个子目录或文件,构成候选集合。
- 对于候选子目录:
- 递归进入该子目录,将其作为新的「当前工作目录」,继续查找其中的
index.md并重复上述过程。 - 在递归过程中,避免一次性深入所有分支,优先沿着与问题最相关的路径向下钻取。
- 递归进入该子目录,将其作为新的「当前工作目录」,继续查找其中的
- 对于候选业务文件(md/文本、PDF、Excel 等):
- 在完成必要的目录层级探索后,收集这些文件为最终的检索目标列表。
- 在优先级排序时:
- 优先选择用途说明与问题主题高度匹配的领域目录和文件
- 其次考虑时间/版本等约束(如果索引中有体现)
- 通用说明类文档(如 README.md、总体设计类文档)放在较后优先级
- 使用一个「当前工作目录」的概念:
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 · 326 lines · 103 tokens per session scan A c97f5a1590cf
知识库 is a skill published in the GitHub repository luna-jmy/thinkdokit-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 103 tokens to every session and 4,438 once invoked, about $0.0005 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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