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 llmwiki-optimizegit 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/llmwiki-optimize)<a href="https://agentmods.dev/skills/luna-jmy/thinkdokit-skills/llmwiki-optimize"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/llmwiki-optimize/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/llmwiki-optimize"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/llmwiki-optimize.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 | $0.00069 | $0.01294 |
| Opus 5 | $0.00034 | $0.00647 |
| Sonnet 5 | $0.00014 | $0.00259 |
| Haiku 4.5 | $0.00007 | $0.00129 |
Grade A, and why
llmwiki-optimize 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki 优化
这个技能不引入新来源，而是让现有 wiki 更紧凑、更清晰、更容易导航。
目标
- 减少重复和碎片化
- 改善页面命名、归类和链接结构
- 把散落在多个页面里的模式提炼成综合页
- 让
index.md更能代表当前知识结构
适用场景
- 页面数量增长后出现重复内容
- 同一主题被拆成太多小页
- 页面名混乱、目录放错位置
- source 页很多，但 synthesis 页很少
- 搜索能搜到内容，但阅读体验很差
优化类别
压缩
- 冗长但信息增量低的页面
- 只是复述来源、缺少综合的摘要页
- 多处重复出现的背景说明
合并
- 名称不同但实质相同的实体页或概念页
- 太小、独立价值不足的页面
- 内容高度重叠的故事页或比较页
重组
type与目录不一致- 文件名不是 kebab-case
- 该在
concepts/的内容跑到了entities/ - frontmatter 缺失或不规范
- frontmatter
tags中缺少llmwiki的应复习页面
链接加固
- 文中提到了页面标题，但没有做成
[[wikilinks]] - 页面间单向链接过多
- 关键页面缺少“相关页面”入口
综合生成
- 多个来源都覆盖、但还没有 synthesis 页的主题
- 多页之间经常一起出现的对比关系
- 值得做成比较页或横向分析页的主题
执行步骤
1. 建立现状视图
- 读
wiki/index.md - 扫描
wiki/下所有页面 - 抽取 frontmatter、链接关系、篇幅、更新时间
- 标记重复、孤立、错位、过长、可综合页面
2. 给出优化计划
在开始改动前，先按类别整理要处理的对象：
- 压缩哪些页面
- 合并哪些页面
- 重组哪些页面
- 加哪些链接
- 新建哪些综合页
如果用户没有限定范围，默认处理全部高收益项。
3. 实施修改
执行时遵守这些约束：
- 合并时保留所有有效来源信息
- 删除冗余页面前先修正所有旧链接
- 重命名或移动后同步更新引用
- 新建 synthesis 页时要体现“共识、分歧、空白”
llmwiki只保留在 frontmattertags中，正文里不要出现#llmwiki；是否保留该标签按原始来源目录判断
4. 重建索引
优化完成后重建 wiki/index.md，保证索引与实际文件一致。
5. 更新搜索索引
如果 qmd 可用，执行索引更新，确保搜索结果与新结构一致。
6. 写日志
记录：
- 压缩了多少页
- 合并了哪些页
- 修复了多少链接
- 新建了哪些 synthesis/comparison 页面
输出要求
给用户的汇报里应说明：
- 哪些改动属于结构性调整
- 哪些页面被合并或重命名
- 哪些新综合页值得优先阅读
- 是否还存在需要人工判断的模糊边界
常用脚本
批量补 frontmatter llmwiki 标签
当优化过程中发现很多页面缺失 frontmatter llmwiki，或正文残留旧标签时，可直接运行：
python3 scripts/ensure_llmwiki_tag.py /path/to/wiki --check
python3 scripts/ensure_llmwiki_tag.py /path/to/wiki
规则：
- 仅处理
wiki/下的 Markdown 页面 - 跳过
index.md和log.md - 只修改 frontmatter
tags - 会顺手清掉正文里残留的
#llmwiki --check只检查，不改文件
按来源收紧 frontmatter llmwiki 标签
如果复习池只想保留 Books/ 知识页，可按原始来源目录批量同步：
python3 scripts/sync_llmwiki_by_source.py /path/to/wiki --check
python3 scripts/sync_llmwiki_by_source.py /path/to/wiki
默认保留这类来源对应页面 frontmatter tags 里的 llmwiki：
Books/
其余页面会移除 frontmatter tags 里的 llmwiki，并清掉正文残留的 #llmwiki。如果项目有别的书籍目录，可追加：
What ships with it
2 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 · 157 lines · 69 tokens per session scan A 5303bb251d29
llmwiki-optimize is a skill published in the GitHub repository luna-jmy/thinkdokit-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 69 tokens to every session and 1,294 once invoked, about $0.0003 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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