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 alpsmonkey/SkillFather --skill datagit clone --depth 1 https://github.com/alpsmonkey/SkillFatherWrote 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/alpsmonkey/skillfather/data)<a href="https://agentmods.dev/skills/alpsmonkey/skillfather/data"><img src="https://agentmods.dev/badge/skills/alpsmonkey/skillfather/data/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/alpsmonkey/skillfather/data"><img src="https://agentmods.dev/badge/skills/alpsmonkey/skillfather/data.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 | $0.00097 | $0.02516 |
| Opus 5.5 | $0.00039 | $0.01006 |
| Sonnet 5.5 | $0.00019 | $0.00503 |
| Haiku 4.5 | $0.00010 | $0.00252 |
Grade A, and why
SkillFather 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 2mo 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
100% identical to SkillFather — 0 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SkillFather - Multi-Platform Agent Skill 适配度分析工具
定位
SkillFather 从使用角度分析一个 Agent Skill 是否适用于当前用户。 仅做适用性评审，不对安全性负责。
评分维度
| 维度 | 权重 | 说明 |
|---|---|---|
| 用例契合度 | 25% | Skill 用途是否匹配用户工作场景 |
| 环境就绪度 | 20% | 所需工具、API、平台是否就绪 |
| 前置条件 | 20% | 依赖、配置、权限是否满足 |
| 工作流匹配 | 20% | 是否融入现有工作流程 |
| 文档质量 | 15% | README 完整度、可操作性 |
使用方式
SkillFather 是一个 Python CLI 工具，本技能指导 Agent 如何调用它。
前置条件
- Python 3.10+ 已安装
- 已执行
pip install git+https://github.com/alpsmonkey/SkillFather.git（或本地pip install -e .） - 安装后命令
python -m skillfather可用
核心流程：选择分析模式
当用户要求分析某个 Skill 时，Agent 必须先让用户选择分析模式，再执行对应的流程。
Step 0：确定 Skill 文件路径
- 如果用户提供了 Skill 路径（文件或目录），直接使用
- 如果用户引用了
@skill:xxx，从 WorkBuddy skills 目录查找：~/.workbuddy/skills/xxx/SKILL.md - 如果用户提供 GitHub URL，提示用户先 clone 到本地
Step 1：让用户选择分析模式
使用 AskUserQuestion 工具向用户展示以下选项：
| 模式 | 说明 | 适用场景 |
|---|---|---|
| 基于记忆分析 | Agent 结合自身记忆（已装技能、工具环境、用户画像）个性化解读评分 | 想要最贴合自己的分析结果 |
| 交互分析 | Agent 逐题提问，用户根据实际情况回答，得到精确评分 | 首次分析、需要深度了解 |
| 自动分析 | 基于 Skill 内容特征自动估算评分，快速出结果 | 快速预览、不需要个性化 |
Step 2：根据用户选择执行对应流程
模式一：基于记忆分析
此模式利用 Agent 自身的记忆和上下文来个性化解读评分。
执行步骤：
-
收集上下文：Agent 读取以下信息构建用户画像：
- 读取 workspace 记忆文件
.workbuddy/memory/MEMORY.md和当日日志 - 列出用户已安装的技能（
~/.workbuddy/skills/目录） - 检查用户常用的工具和环境（通过记忆中的偏好信息）
- 读取
~/.workbuddy/MEMORY.md获取跨项目偏好
- 读取 workspace 记忆文件
-
运行 CLI 分析：
python -m skillfather analyze <skill_path> --format console -
个性化解读：Agent 基于收集到的上下文，对 CLI 输出的每个维度评分进行个性化解读：
- 用例契合度：结合用户日常工作内容（如 SAP 分析、前端开发等）判断该 Skill 是否匹配
- 环境就绪度：结合用户已装技能和工具，判断所需依赖是否就绪
- 前置条件：结合用户记忆中的配置信息（API Key、已连接的服务等）
- 工作流匹配：结合用户的工作习惯和已用工具链，判断是否融入
- 文档质量：Agent 自行评估文档的完整性和可操作性
-
输出格式：Agent 以 Markdown 表格 + 文字解读的方式呈现最终结论，每个维度给出：
- 原始分数（CLI 输出）
- 个性化调整理由（基于记忆）
- 最终建议分数
-
总结：给出是否推荐安装的结论，以及需要特别注意的前置条件或适配事项
模式二：交互分析
此模式由 Agent 逐题提问，用户回答后计算精确评分。
执行步骤：
- 运行 CLI 分析获取题目：
记录 CLI 输出的所有诊断问题。python -m skillfather analyze <skill_path> --format console
What ships with it
1 file 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.
- 2mo ago First seen · 246 lines · 97 tokens per session scan A 1184426e307b
SkillFather is a skill published in the GitHub repository alpsmonkey/SkillFather (2 stars, last pushed 2mo ago), licensed MIT. It adds 97 tokens to every session and 2,516 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to SkillFather, differing in 0 lines, and is treated as a copy.
SkillFather compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| SkillFatheralpsmonkey/SkillFather | Skill | 2 | 2mo ago | MIT | A | 97 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |