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 grasscaograss/AwesomeWeldoneSkills --skill knowledge-reorggit clone --depth 1 https://github.com/grasscaograss/AwesomeWeldoneSkillsWrote 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/grasscaograss/awesomeweldoneskills/knowledge-reorg)<a href="https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/knowledge-reorg"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/knowledge-reorg/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/grasscaograss/awesomeweldoneskills/knowledge-reorg"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/knowledge-reorg.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 | $0.00096 | $0.02539 |
| Opus 5 | $0.00048 | $0.01269 |
| Sonnet 5 | $0.00019 | $0.00508 |
| Haiku 4.5 | $0.00010 | $0.00254 |
Grade A, and why
knowledge-reorg 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 9d 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 — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Reorg
知识库位于 archive/knowledge/，按领域组织目录。本技能提供领域级结构操作与健康检查。
知识库结构
archive/knowledge/
├── dual-arm/ ← 双臂系统
├── weld-template/ ← 焊接模板
├── weld-seam/ ← 焊缝规划
├── coarse-positioning/ ← 粗定位
├── scanning/ ← 精定位与扫描
├── capacity/ ← 产能统计
├── weld-tracking/ ← 焊接跟踪
├── coordinate/ ← 坐标与矩阵
├── workflow/ ← 状态机与工作流
├── frontend/ ← 前端界面
├── device-robot/ ← 设备与机器人
└── tools/ ← 工具与其他
知识文件格式
每个 .md 文件必须包含 YAML frontmatter：
---
name: kebab-case-slug
description: 一句话摘要
metadata:
type: knowledge
---
# 标题
## 交叉引用
- 相关概念见 [[other-file-name]]
命令语法
/knowledge-reorg ← 无参数：执行 inspect
/knowledge-reorg inspect ← 健康检查
/knowledge-reorg merge <domain-a> into <domain-b> ← 合并两个领域
/knowledge-reorg split <domain> → <new-a>, <new-b> ← 拆分领域（agent 驱动）
/knowledge-reorg move <file> to <domain> ← 跨领域移动文件
/knowledge-reorg consolidate <domain> ← 合并碎片文件（agent 驱动）
领域名对应 archive/knowledge/ 下的目录名（如 dual-arm、weld-seam）。文件名不含扩展名（如 strategy、arc-timing）。
inspect — 健康检查
扫描所有领域文件夹，逐项报告以下指标：
| 检查项 | 条件 | 级别 | 建议 |
|---|---|---|---|
| 领域膨胀 | 文件数 > 10 | ⚠️ 警告 | 建议拆分为子领域 |
| 孤立领域 | 文件数 = 1 | ⚠️ 警告 | 建议合并到语义最接近的领域 |
| 交叉引用断链 | [[name]] 指向不存在的文件 |
🔴 错误 | 报告断链位置与目标名 |
| 缺少 frontmatter | 文件不以 --- 开头或缺少 name/description/metadata.type |
🔴 错误 | 报告缺失字段 |
| 重复 name | 两个文件的 frontmatter name 相同 |
🔴 错误 | 报告冲突文件 |
输出格式
以表格形式呈现每个领域的检查结果：
领域 文件数 警告 错误 详情
dual-arm 5 0 0
weld-seam 5 0 1 断链: [[nonexistent]] (planning.md L42)
weld-tracking 1 1 0 建议: 合并到相邻领域
workflow 7 0 0
对每个问题附上具体位置（文件名 + 行号），便于定位修复。
执行步骤
- 列出
archive/knowledge/下所有子目录 - 遍历每个目录内的
.md文件 - 解析 frontmatter，检查格式完整性
- 提取所有
[[...]]交叉引用，验证目标文件是否存在 - 汇总为报告，按领域分组展示
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.
- 9d ago First seen · 249 lines · 96 tokens per session scan A 9b20ab4ca71b
knowledge-reorg is a skill published in the GitHub repository grasscaograss/AwesomeWeldoneSkills (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 96 tokens to every session and 2,539 once invoked, about $0.0005 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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