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alchaincyf alchaincyf
from GitHub Content & Multimedia
phase 女娲 我想提升决策质量

huashu-nuwa

女娲造人：输入人名/主题/甚至只是模糊需求，自动深度调研→思维框架提炼→生成可运行的人物Skill。 两种入口：(1)明确人名→直接蒸馏 (2)模糊需求→诊断推荐→再蒸馏。 触发词：「造skill」「蒸馏XX」「女娲」「造人」「XX的思维方式」「做个XX视角」「更新XX的skill」。 模糊需求也触发：「我想提升决策质量」「有没有一种思维方式能帮我...」「我需要一个思维顾问」。 --- # 女娲 · Skill造人术 > 「写不进去的那部分，才是你真正的护城河。」——但写得进去的部分，已经足够强大。 ## 核心理念 女娲不是复制人，是**提炼思维框架**。 一个好的人物Skill是一套可运行的认知操作系统： - 他用什么**心智模型**看世界？（镜片） - 他用什么**决策启发式**做判断？（直觉规则） - 他怎么**表达**？（DNA） - 他**绝对不会**做什么？（反模式） - 什么是这个Skill**做不到的**？（诚实边界） **关键区分**：捕捉的是HOW they think，不是WHAT they said。 --- ## 执行流程 ### Phase 0: 入口分流 收到用户输入后，先判断属于哪条路径： | 用户输入 | 路径 | 示例 | |---------|------|------| | 明确的人名/主题 | **直接路径** → Phase 0A | 「蒸馏芒格」「做一个费曼skill」 | | 模糊的需求/困惑 | **诊断路径** → Phase 0B | 「我想提升决策质量」「有没有一种思维方式能帮我看透商业本质」 | --- ### Phase 0A: 需求澄清（直接路径） 收到明确名字后，确认： 1. **这个人/主题是谁**：确保理解正确 2. **聚焦方向**（可选）：全面画像 vs 聚焦某个维度？ 3. **用途**：思维顾问？决策参考？角色扮演？ 4. **新建 or 更新**：是否已有该人物的Skill？（检查 `.claude/skills/` 目录） 用户说「就做XX」没有更多信息 → 默认全面画像 + 思维顾问，直接推进。 确认后 → 跳到 Phase 0.5。 --- ### Phase 0B: 需求诊断（模糊路径） 用户不知道该蒸馏谁，只有需求或困惑。这时女娲的工作是**从需求反推最合适的蒸馏对象**。 #### Step 1: 需求定位 通过1-2个追问，定位用户的核心需求维度： | 需求维度 | 典型表达 | 思维框架方向 | |---------|---------|------------| | 决策与判断 | 「怎么做更好的决策」「总是选错」「分析瘫痪」 | 多元思维模型、逆向思考、概率思维 | | 表达与写作 | 「想把复杂的事说清楚」「文章没人看」「写得无聊」 | 费曼式简化、故事化思维、类比能力 | | 创业与商业 | 「想做独立开发」「商业模式想不通」「找不到PMF」 | 第一性原理、杠杆思维、产品克制 | | 教学与传播 | 「讲课没人听」「学生理解不了」「知识传递效率低」 | 从已知到未知、隐喻教学、最少必要知识 | | 批判思维 | 「总被忽悠」「想识别不靠谱的说法」「看不透本质」 | 证伪思维、演化论视角、认知偏差识别 | | 内容创作 | 「做视频没流量」「不知道拍什么」「内容没特色」 | 注意力工程、测试迭代、受众心理 | | 人生策略 | 「职业方向迷茫」「时间总不够」「焦虑」 | 长期主义、杠杆选择、复利思维 | | 风险与不确定性 | 「怎么应对黑天鹅」「投资总亏」「太保守/太冒险」 | 反脆弱、凸性策略、尾部风险管理 | | 设计与产品 | 「用户体验差」「产品没特色」「不知道做减法」 | 极简主义、用户心理模型、约束即创意 | | 幽默与表达力 | 「说话没意思」「想让内容更有趣」「太严肃了」 | 荒诞对比、预期违背、自嘲式权威 | 追问原则： - 最多问2轮，不要变成问卷调查 - 如果用户已经表达得足够清晰，不追问，直接推荐 - 追问的目的是区分相似维度（比如「决策」是商业决策还是人生决策？） **示例对话**（展示诊断节奏）： ``` 用户：我总觉得自己做决定太慢，想来想去最后还是选错 女娲：你说的决策主要是哪种场景？比如商业/投资决策，还是职业/人生方向的选择？ 用户：主要是商业上的，比如要不要做某个产品、要不要接某个合作 女娲：明白了，你的核心需求是「在信息不完整时快速做出高质量的商业判断」。 我推荐3个候选： [展示候选推荐...] ``` 注意节奏：一轮追问定位场景 → 确认需求 → 直接推荐。不要第三轮还在问。 #### Step 2: 候选推荐 基于需求维度，推荐2-3个候选方案。候选可以是人物，也可以是主题。

⬇1 ❤938 2 days ago · Downloaded Detail →
BuildGreatProducts BuildGreatProducts
from GitHub Development & Coding
phase product building

plaid-build

Product Led AI Development — Build mode. Reads the product roadmap and builds the app phase by phase, referencing the PRD for implementation details. After each phase, reviews code for issues, then commits to git. Continues until all phases are complete. Use when someone says "plaid build", "build the app", "start building", "execute the roadmap", "build phase", or "continue building". For product planning, see plaid-plan. For go-to-market, see plaid-launch.

⬇0 ❤34 9 days ago · Uploaded Detail →
myrtlepn myrtlepn
from GitHub Tools & Productivity
automation phase mst

accept

완료된 결과물을 최종 수락합니다 (Phase 3 → Phase 5). Worktree를 main에 머지하고 정리합니다. 사용자가 '수락', '머지', '최종 수락'을 말하거나 /mst:accept를 호출할 때 사용. 기본적으로 /mst:approve에서 자동 호출되며, workflow.auto_accept_result=false 시 수동 사용.

⬇0 ❤21 4 days ago · Uploaded Detail →

Skill File Structure Sample (Reference)

skill-sample/
├─ SKILL.md              ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json  ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample        ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│  └─ example-run.py     ✅ Runnable example script for quick verification
├─ assets/
│  ├─ example-formatting-guide.md  🧩 Output conventions: layout / structure / style
│  └─ example-template.tex         🧩 Templates: quickly generate standardized output
└─ references/           🧩 Knowledge base: methods / guides / best practices
   ├─ example-ref-structure.md     🧩 Structure reference
   ├─ example-ref-analysis.md      🧩 Analysis reference
   └─ example-ref-visuals.md       🧩 Visual reference

More Agent Skills specs Anthropic docs: https://agentskills.io/home

SKILL.md Requirements

├─ ⭐ Required: YAML Frontmatter (must be at top)
│  ├─ ⭐ name                 : unique skill name, follow naming convention
│  └─ ⭐ description          : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│  ├─ ✅ license              : license identifier
│  ├─ ✅ compatibility        : runtime constraints when needed
│  ├─ ✅ metadata             : key-value fields (author/version/source_url...)
│  └─ 🧩 allowed-tools        : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
   ├─ ✅ Overview / Purpose
   ├─ ✅ When to use
   ├─ ✅ Step-by-step
   ├─ ✅ Inputs / Outputs
   ├─ ✅ Examples
   ├─ 🧩 Files & References
   ├─ 🧩 Edge cases
   ├─ 🧩 Troubleshooting
   └─ 🧩 Safety notes

Why SkillWink?

Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.

We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.

Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

Quick Start:

Import/download skills (.zip/.skill), then place locally:

~/.claude/skills/ (Claude Code)

~/.codex/skills/ (Codex CLI)

One SKILL.md can be reused across tools.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.

Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.

2. How do Skills work?

Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.

This keeps agents lightweight while preserving enough context for complex tasks.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared across tools?

Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.

Example: retrieval + writing + automation scripts as one workflow.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up