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 lihaozheCharlie/TwhWiki --skill querygit clone --depth 1 https://github.com/lihaozheCharlie/TwhWikiWrote 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/lihaozhecharlie/twhwiki/query)<a href="https://agentmods.dev/skills/lihaozhecharlie/twhwiki/query"><img src="https://agentmods.dev/badge/skills/lihaozhecharlie/twhwiki/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/lihaozhecharlie/twhwiki/query"><img src="https://agentmods.dev/badge/skills/lihaozhecharlie/twhwiki/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 | $0.00039 | $0.00738 |
| Opus 5 | $0.00019 | $0.00369 |
| Sonnet 5 | $0.00008 | $0.00148 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
consume-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 12d 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
消费：查询
当用户询问 wiki 已知内容、请求综合某个人物/事件/城市/阶段/系统，或要求在对话中使用 wiki 时使用。
本 Skill 严格只读。查询发现缺失或陈旧内容时，可以建议后续动作；除非用户另行明确要求修改，否则不得改动 wiki。
检索顺序
- 从
wiki/index.md和最具体的综合 wiki 页面开始。 - 沿内部链接读取相关页面。
- 回答需要证据时，通过
wiki/08 来源索引/查找原始笔记。 - 只有综合页面不足，或用户要求原始证据时，才检索
原始知识库/。
解释性查询与人物视角
- 事实查找、导航、原句核验和“有哪些页面”使用强度 0，不加载人物视角。
- 用户询问“怎样理解、为什么、这说明什么、我该怎么看”，或明确指定某个人物时，读取
skills/common/reasoning-lenses/SKILL.md。 - 运行
python3 skills/common/reasoning-lenses/scripts/list_lenses.py动态发现当前全部人物，不维护固定名单。 - 未指定人物时，根据问题选择 1 个会实质改变注意力与推理的主视角，通常最多 1 个辅助视角。默认不展示人物姓名，只给出独立成立的理解。
- 用户明确要求比较多人时，分别完整推演各视角，再说明分歧来自哪里；不要合并成平均意见。
- 人物视角只解释已有证据。查询仍然严格只读，不能因得到新洞见而写入 Wiki。
回答规则
- 区分有来源事实、综合判断和推断。
- 优先给出简洁回答，并链接相关 wiki 页面。
- 如果消息增加了可沉淀的个人知识或指出规则问题，回答后说明合适的后续动作，不要自动写入。
- 区分解释/诊断请求与修改请求。
- 解释性回答先保持事实边界，再让主视角决定怎样理解；不得把视角推断写成日记事实。
- 去掉人物姓名和风格词后，推理仍应可辨认且有证据支撑。
读取路径
- 读取
wiki/index.md或相关分区页。 - 读取目标综合页。
- 只有需要证据或核验判断时，才回到
原始知识库/。 - 对话来源材料读取
wiki/08 来源索引/对话分析索引.md。
证据优先级
- 原始日记或来源笔记。
- 用户直接提供并标注为对话的材料。
- 既有 wiki 综合。
- 有明确来源的外部信息。
输出
- 直接回答问题，并链接相关综合页面。
- 标记推断，区分对话材料和日记证据。
- 如果修复有帮助，将其描述为可选后续动作，但不要执行修改。
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.
- 12d ago First seen · 56 lines · 39 tokens per session scan A 3e384495d222
consume-query is a skill published in the GitHub repository lihaozheCharlie/TwhWiki (24 stars, last pushed 7d ago), licensed MIT. It adds 39 tokens to every session and 738 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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