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 lululu811/init-knowledge-base --skill querygit clone --depth 1 https://github.com/lululu811/init-knowledge-baseWrote 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/lululu811/init-knowledge-base/query)<a href="https://agentmods.dev/skills/lululu811/init-knowledge-base/query"><img src="https://agentmods.dev/badge/skills/lululu811/init-knowledge-base/query/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/lululu811/init-knowledge-base/query"><img src="https://agentmods.dev/badge/skills/lululu811/init-knowledge-base/query.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 | $0.00066 | $0.00599 |
| Opus 5.5 | $0.00026 | $0.00240 |
| Sonnet 5.5 | $0.00013 | $0.00120 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
query 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.
What it actually says
query 技能
核心目标
将用户的提问转化为对本地 Wiki 的深度检索。提取相关页面信息，综合出带有明确引用来源的双链回答。
触发场景
- 用户输入
/query <问题> - 用户询问关于知识库、笔记、记录中的内容
- 用户提及 wiki、知识库、笔记等关键词
降级策略
如果知识库中无相关内容：
本地知识库中未找到相关内容，以下为通用知识回答：[直接回答]
检索与综合流水线
步骤 1：查阅全局索引
首选路径：读取 wiki/index.md，定位与问题相关的 Entities、Concepts、Sources、Syntheses。
备选路径：如果 index.md 无法定位或内容不足，直接扫描 wiki/ 目录下的 .md 文件列表，通过文件名和 frontmatter 中的 tags、type 字段筛选相关页面。
步骤 2：深度阅读目标文件
选取步骤 1 中找到的最相关页面，使用读取工具获取完整内容。
步骤 3：综合与回答
双链引用规范：
- 每当引用 Wiki 页面的信息，在文本中使用
[[页面名称]]标注 - 引用同一页面：段落首尾各引用一次
- 引用特定原文：使用 Markdown 块引用
> 引用内容
步骤 4：高价值内容固化
如果回答超过 2 个段落且具有分析价值，主动询问用户是否保存到 wiki/syntheses/。
用户同意后，按照 CLAUDE.md 规范创建文件并更新 wiki/index.md。
步骤 5：记录操作日志
查询结束后必须在 wiki/log.md 末尾追加：
## [YYYY-MM-DD] query | <操作简述>
- **输出**: <引用页面列表或"即时回答未保存">
强制约束
- 禁止凭记忆回答：必须先检索知识库
- 禁止过度引用：同一页面信息在段落首尾引用一次即可
- 禁止静默回答：知识库无相关内容时必须声明
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 · 58 lines · 66 tokens per session scan A 7e86a5b782b0
query is a skill published in the GitHub repository lululu811/init-knowledge-base (23 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 599 once invoked, about $0.0003 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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