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 TashanGKD/cognitive-os --skill cognitive-reorganizegit clone --depth 1 https://github.com/TashanGKD/cognitive-osWrote 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/tashangkd/cognitive-os/cognitive-reorganize)<a href="https://agentmods.dev/skills/tashangkd/cognitive-os/cognitive-reorganize"><img src="https://agentmods.dev/badge/skills/tashangkd/cognitive-os/cognitive-reorganize/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/tashangkd/cognitive-os/cognitive-reorganize"><img src="https://agentmods.dev/badge/skills/tashangkd/cognitive-os/cognitive-reorganize.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 | $0.00230 | $0.07185 |
| Opus 5 | $0.00115 | $0.03592 |
| Sonnet 5 | $0.00046 | $0.01437 |
| Haiku 4.5 | $0.00023 | $0.00719 |
Grade A, and why
cognitive-reorganize 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.
This is a copy
94% identical to cognitive-reorganize — 48 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 519 lines — stays where its author put it; the contents beside it link to each section on GitHub.
认知结构重组 Skill（Cognitive Reorganize）
这个 Skill 编码了「如何从一组散落文档出发，构建完整自洽的认知结构」的完整方法论。 基于 2026-03-19 实际执行过程提炼，见过程记录：
认知结构/L3_原始记录/对话记录/认知结构整理过程记录_20260319.md
与其他 Skill 的区别
| Skill | 适用场景 |
|---|---|
cognitive-capture-fragment |
捕捉单个新碎片 |
cognitive-integrate-fragments |
处理积压的待整合碎片 |
cognitive-reorganize |
从零/从大量散落文档构建/重构整个认知结构 |
cognitive-consistency-check |
验证已有认知结构是否自洽 |
激活后立即执行
第零步：创建外部记忆工作草稿
Write: 认知结构/工作草稿_知识图谱构建.md（见文件格式）
作用：AI多轮阅读之间的持久化记忆，不写草稿=信息丢失
第零点五步：检查认知结构现有状态（F3修复，2026-03-19）
在扫描任何外部文档之前，先检查 认知结构/ 目录本身：
Step a 枚举 认知结构/ 一级子目录
→ 对照 C11 合法目录列表（见维护协议）
→ 发现任何游离目录 → 立即标记，纳入本次整理范围
Step b 枚举 认知结构/技术架构/（如存在这类特殊目录）
→ 检查其中每个文档是否有对应的 L1/L2 归类
→ 未归类的 → 加入本次 Round A 扫描范围
Step c 检查现有分类清单的 ◑ PENDING 项
→ 这些文档在本次整理中应被处理或主动标记为 ⏸️ DEFERRED
Step d ⚠️【单文件询问时执行】若触发来源是对「某具体文件」的询问（用户提供了文件名或路径）：
对该被询问文件执行快速四轴分类，输出推荐结论：
轴一（Loop归属）判断：
「这个文件是关于『如何执行某类任务』的规范/指南吗？」
→ 是 = Loop1（执行规范目录，不迁入认知结构）
「这是某个具体工作任务的输入或输出吗？」
→ 是 = Loop3（项目工作目录，不迁入认知结构）
→ 若含有认知价值段落 → 建议：提取碎片 → cognitive-capture-fragment
上述均否 → Loop2（认知结构）→ 继续轴二判断
轴二（认知层次）判断（Loop2 文档）：
含原创观点/洞见/框架？→ L1（系统性文档）或 L2（碎片化思考）
外部调研/参考资料？→ REF-EXT（轻量写入协议）
提炼了底层行为规律？→ L1.5（候选原则）
轴三（领域维度）判断（L1/REF-EXT 文档）：
产品机会/用户需求/商业模式 → 产品理论维度
团队/组织/协作/分工 → 组织理论维度
科研方法/实验设计/学术 → 研究范式维度
大脑认知/学习/记忆/神经科学 → 认知科学基础维度
工程/代码/架构/部署/系统 → 系统架构思维维度
写作/表达/传播/个人方法 → 个人方法论维度
自我反思/行为模式 → 自我认知维度
跨多个领域 → 选主要领域，备注关联
输出推荐结论（格式）：
「📍 分类建议：
Loop归属：[Loop1 / Loop2 / Loop3]
层次：[L1 / L1.5 / L2 / REF-EXT / Loop1-规范 / Loop3-工作产物]
维度：[具体维度名]（Loop2-L1/REF-EXT 时填写）
目标路径：[具体建议路径]
写入方式：[完整迁移8步（L1）/ 轻量写入3步（REF-EXT）/ cognitive-capture-fragment（L2）/ 保持原位（Loop1/Loop3）]
是否现在执行？[执行] [留待后续]」
→ 用户选「执行」→ 按写入方式执行，或启动完整重组流程
→ 用户选「留待后续」→ 将该文件添加到分类清单中（状态：◑ PENDING，含建议路径备注）
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 · 519 lines · 230 tokens per session scan A debba626eecb
cognitive-reorganize is a skill published in the GitHub repository TashanGKD/cognitive-os (9 stars, last pushed 5mo ago), licensed MIT. It adds 230 tokens to every session and 7,185 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to cognitive-reorganize, differing in 48 lines, and is treated as a copy.
Other skills, from other repositories
cognitive-ask
A question-answering workflow that answers from a user's own knowledge documents, with sources, confidence levels, contradictions, and gaps made clear.
cognitive-reorganize
A workflow for reorganising scattered documents into a complete personal knowledge structure.
cognitive-extract-principle
A workflow for finding shared patterns across several stored thought fragments and turning them into candidate principles for review.
cognitive-integrate-fragments
A workflow for moving pending thought fragments into broader knowledge documents while preserving the existing structure.
cognitive-self-reflect
A guided self-reflection process that turns vague observations about your habits or feelings into structured records and compares them with earlier entries.
cognitive-capture-fragment
A workflow for capturing brief ideas and storing them as structured entries in a personal knowledge system.