Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.
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 foryourhealth111-pixel/Vibe-Skills --skill knowledge-stewardgit clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-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/foryourhealth111-pixel/vibe-skills/knowledge-steward)<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/knowledge-steward"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/knowledge-steward/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/foryourhealth111-pixel/vibe-skills/knowledge-steward"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/knowledge-steward.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 | $0.00085 | $0.03277 |
| Opus 5 | $0.00043 | $0.01639 |
| Sonnet 5 | $0.00017 | $0.00655 |
| Haiku 4.5 | $0.00009 | $0.00328 |
Grade A, and why
knowledge-steward 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 — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Steward Skill
你的"数字记账员"——防止智力剩余价值随着电缆流失。将稍纵即逝的灵感、有效的提示词、踩过的坑和突然的顿悟转化为永久存储的知识资产，并自动备份到GitHub云端。
When to Use This Skill
当用户想要保存以下内容时使用此技能：
- 提示词复盘：发现某个Prompt效果惊人地好或差时
- 触发词："保存这个提示词"、"save this prompt"、"记录这个Prompt"
- 工程排坑：花了很长时间解决了一个Bug时
- 触发词："记录这个Bug"、"save this bugfix"、"保存解决方案"
- 灵感闪现：突然想到一个架构优化或设计模式时
- 触发词："保存这个想法"、"capture this idea"、"记录这个灵感"
- 模式总结：发现了一个可复用的代码模式或最佳实践时
- 触发词："保存这个模式"、"save this pattern"、"记录这个实践"
- 效率优化：找到了提升工作效率的方法时
- 触发词："保存这个技巧"、"save this tip"、"记录这个优化"
- 工作流复盘：分析autonomous-builder的工作流报告时
- 触发词："分析工作流"、"复盘这个项目"、"总结开发过程"
- 架构经验提取：从多个报告中提取架构模式时
- 触发词："提取架构模式"、"总结设计决策"、"分析技术选型"
通用触发词：
- "保存到Obsidian"
- "记录这个"
- "save this insight"
- "memo this"
- "capture this"
Not For / Boundaries
不适用于：
- 纯粹的对话或提问（没有需要保存的内容）
- 已经保存在其他地方的内容（除非用户明确要求）
- 敏感信息或密钥（会警告用户）
必需输入：
- 标题：如果用户没有明确标题，从内容中提取
- 类型：从触发词或内容推断（提示词/模式/问题修复/想法/效率优化）
- 内容：从对话上下文中捕获
可选输入：
- 额外的标签
- 自定义分析
Quick Reference
使用模式
模式1：保存提示词
用户："Claude，把你刚才用的那个关于代码重构的Prompt保存下来，标记为'高效'。"
Claude：提取最近使用的提示词 → 生成分析 → 保存到 提示词/ 目录
模式2：记录Bug解决方案
用户："记录这个Bug的解决方案，别让我下次再踩坑。"
Claude：捕获问题描述和解决方案 → 分析根本原因 → 保存到 问题修复/ 目录
模式3：捕获灵感
用户："保存这个关于微服务解耦的想法。"
Claude：提取想法内容 → 生成可行性分析 → 保存到 想法/ 目录
模式4：中文触发
用户："保存到Obsidian：使用苏格拉底式提问来引导代码重构"
Claude：识别中文触发词 → 提取标题和内容 → 自动分类 → 保存
文件结构
保存的笔记包含：
- YAML Frontmatter：元数据（创建时间、类型、标签、状态）
- 标题：清晰的描述性标题
- 背景（Context）：当时在做什么
- 内容（Content）：核心的提示词/代码/想法
- 分析（Analysis）：苏格拉底式反思
目录组织
D:\Documents\ai技能外置大脑/
└── Claude_Insights/
├── 提示词/ # Prompts - 有效/无效的提示词
├── 模式/ # Patterns - 可复用的代码模式
├── 问题修复/ # Bugfixes - Bug解决方案
├── 想法/ # Ideas - 架构和设计想法
├── 效率优化/ # Efficiency - 提升效率的技巧
├── 工作流/ # Workflows - AI辅助开发工作流分析
└── 架构决策/ # Architecture - 架构设计决策记录
Examples
Example 1: 保存高效提示词
Input:
用户："Claude，保存这个提示词：'请用苏格拉底式提问引导我重构这段代码，不要直接给出答案'。这个提示词让我自己思考得更深入了。"
What ships with it
14 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.
- .gitignore 202 B
- assets/note-template.md 1.7 KB
- assets/setup-guide.md 8.0 KB
- assets/workflow-analysis-template.md 675 B
- config.example.yaml 2.3 KB
- README.md 723 B
- references/index.md 8.4 KB
- scripts/distill_experience.py 8.1 KB runs code
- scripts/git_sync.py 12 KB runs code
- scripts/init_git_repos.py 9.1 KB runs code
- scripts/parse_workflow_report.py 4.9 KB runs code
- scripts/save_to_obsidian.py 12 KB runs code
- scripts/setup_github.py 7.9 KB runs code
- scripts/sync_skill_code.py 4.9 KB runs code
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 · 331 lines · 85 tokens per session scan A 28f445c13ea9
knowledge-steward is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,252 stars, last pushed 12d ago), licensed Apache-2.0. It adds 85 tokens to every session and 3,277 once invoked, about $0.0004 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 2026-09-03.
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