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-capture-fragmentgit 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-capture-fragment)<a href="https://agentmods.dev/skills/tashangkd/cognitive-os/cognitive-capture-fragment"><img src="https://agentmods.dev/badge/skills/tashangkd/cognitive-os/cognitive-capture-fragment/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-capture-fragment"><img src="https://agentmods.dev/badge/skills/tashangkd/cognitive-os/cognitive-capture-fragment.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 | $0.00058 | $0.02639 |
| Opus 5 | $0.00029 | $0.01319 |
| Sonnet 5 | $0.00012 | $0.00528 |
| Haiku 4.5 | $0.00006 | $0.00264 |
Grade A, and why
cognitive-capture-fragment 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
碎片捕捉 Skill(Capture Fragment)
把用户随时产生的碎片想法,经过关卡A(新洞见判断)后,结构化写入L2碎片层,并更新索引和系统日志。
知识导航表(执行前必须理解的概念根)
| 层级 | 文档 | 需要理解的概念 |
|---|---|---|
| D0 认知根(必读) | cognitive/L1_knowledge/formal_spec/self_evolving_agent_spec.md |
层1:K-object定义(编码陈述性事实的知识对象);层2:D_op.create(对象应存在但不存在);层7:完备题库维度——对象类型 × 操作类型 × 关系类型 |
| D3 规范参考 | cognitive/maintenance_protocol.md |
碎片写入规范:命名格式/存放位置/索引更新要求 |
| D4 运行时数据 | cognitive/L2_fragments/fragment_index.md + L0_大脑总地图.md |
当前最大碎片ID(F-XXX)+ 整体认知体系地图(确定碎片归属域) |
核心概念速查: ① K-object.create(捕捉碎片)= 系统中尚不存在的知识,需要新建一个K-object来编码它 ② L2碎片 = K-object的fragment子类,是L1框架文档的上游原材料,待整合 ③ 写入后必须更新碎片整合索引——实现C1(完全可观测性:所有对象必须在R中注册)
激活后立即执行(顺序不可跳过)
Step 1 读取上下文
Read: cognitive/L2_fragments/fragment_index.md
→ 获取当前最大碎片ID(F-XXX),下一个ID = F-(N+1)
Read: cognitive/L0_brain_map.md(摘要,了解当前知识体系)
Read: cognitive/document_catalog.md(快速扫描,识别与当前话题相关的已有文档)
→ 若发现分类清单中有与当前碎片主题高度相关的已有文档(★CURRENT 或 ⏸️DEFERRED):
提示用户「已有相关文档:[文档名] / [Loop归属] / [状态],是补充该文档还是记录新碎片?」
→ 用户选"补充已有文档" → 结束本 Skill,引导至 cognitive-update-knowledge
→ 用户选"记录新碎片" → 继续 Step 2
Step 2 理解用户输入
→ 用户说的是完整想法,还是需要追问才能清楚?
→ 如果不够清楚,追问一个最关键的问题再继续(不要追问多个)
Step 3 [关卡A] 判断是否有新洞见
→ 快速比对碎片整合索引中的已有标题,判断是否与已有内容高度重复
→ 如果高度重复(语义相似度>80%):
「此内容与碎片[F-XXX]「...标题...」高度相似。是追加补注,还是确实是新视角?」
→ 用户说"追加" → 在原碎片文件对应条目末尾追加注释,更新索引,写日志,结束
→ 用户说"新的" → 继续 Step 4
→ 如果是新洞见:继续 Step 4
Step 4 推断碎片属性
根据内容推断:
- 类型:product_theory(产品理论)| self_reflection(自我反思)| ai_review(AI复盘)
org_design(组织设计)| methodology(思维方法)
- 对应L1文档(初步关联):[A]产品框架 / [B]产品定位 / [B']产品设计 / [C]协作模式 /
[D]元框架 / [E]文档体系 / 个人思维方法论 / 个人认知模式
- 对应L1.5原则:P1(验证优先于感受)/ P2(从小点切入升维)/ 无
- 确认程度:confirmed(确信)/ tentative(暂定)/ uncertain(存疑)
Step 5 生成结构化碎片并向用户确认
展示:
「准备记录碎片 [F-新ID]:
标题:「...」
类型:[类型]
归因:🔵 用户原始思考
关联L1:[X]
关联L1.5:P? / 无
确认程度:[确认程度]
[确认记录] [修改后记录]」
Step 5 用户确认写入后,正式将碎片写入 L2 文件
(按 cognitive-l3-auto-log 规则,写入后自动追加系统日志)
Step 5.5 【F-022 全节点挑战者反思】用户确认后、正式写入前执行
以「认知体系一致性守门人」视角执行3条挑战:
1. 矛盾检测:这条碎片的核心观点,与 L1.5 已确认原则(P1/P2)或 L1 文档中
任何已有结论有没有张力(不一定是矛盾,但可能需要说明关系)?
2. 置信度诚实:碎片中有没有「用确定语气说了一个实际上是推断的结论」?
如果有,应该在碎片中标注「推断/待验证」而非写成已确认事实。
3. 级联缺失:写入这条碎片后,是否有任何关联的 L1 文档应该被标注为「需重新审视」,
但目前碎片的关联字段没有指向它?
若发现可修复的问题(措辞/置信度/关联)→ 先修改碎片内容,再写入
若确实无重大问题 → 继续写入
Step 5.8 L2 积累阈值监控(CS-014 修复,写入后检查,静默执行)
Read: cognitive/L2_fragments/fragment_index.md(快速计数)
统计 🔲 待整合 状态的碎片总数 N
IF N ≥ 8:
「💡 当前积累了 N 条待整合碎片。建议触发 cognitive-integrate-fragments 处理。
[立即整合] [稍后处理]」
IF N < 8:静默,不输出任何提示
Step 6 执行写入(用户确认后)
a. Write 到对应的L2文件(追加到文件末尾):
- product_theory/self_reflection/ai_review/org_design/methodology
→ 文件路径:cognitive/L2_fragments/[类型目录]/[文件名].md
b. 更新碎片整合索引.md(追加一行:ID | 标题 | 类型 | 关联L1 | L1.5原则 | 🔲待整合 | 时间)
c. 追加 cognitive/L3_logs/system_log.md:
[LOG-今日日期-NN] cognitive-capture-fragment | 记录碎片[F-ID]「标题」 | L2碎片文件+索引
Step 7 收尾反馈
「✅ 碎片 [F-ID] 已记录。
当前待整合碎片:N 个
[现在整合最近的碎片] [稍后处理]」
→ 如果用户选择"现在整合",触发 cognitive-integrate-fragments Skill
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 · 186 lines · 58 tokens per session scan A c334cdc8bc49
cognitive-capture-fragment is a skill published in the GitHub repository TashanGKD/cognitive-os (9 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 2,639 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.
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.