nuwa-skill
Nuwa (女娲): Input any name, auto-research → extract thinking frameworks → generate a runnable perspective skill. Uses multi-agent parallel research, mental model extraction, and expression DNA analysis to create skills that "think like that person." Trigger: "create a perspective skill for X", "distill X", "nuwa", "make a skill for X", "X's thinking framework"
Best use case
nuwa-skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Nuwa (女娲): Input any name, auto-research → extract thinking frameworks → generate a runnable perspective skill. Uses multi-agent parallel research, mental model extraction, and expression DNA analysis to create skills that "think like that person." Trigger: "create a perspective skill for X", "distill X", "nuwa", "make a skill for X", "X's thinking framework"
Teams using nuwa-skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/nuwa-skill/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How nuwa-skill Compares
| Feature / Agent | nuwa-skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Nuwa (女娲): Input any name, auto-research → extract thinking frameworks → generate a runnable perspective skill. Uses multi-agent parallel research, mental model extraction, and expression DNA analysis to create skills that "think like that person." Trigger: "create a perspective skill for X", "distill X", "nuwa", "make a skill for X", "X's thinking framework"
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
Best AI Skills for ChatGPT
Find the best AI skills to adapt into ChatGPT workflows for research, writing, summarization, planning, and repeatable assistant tasks.
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
AI Agent for Product Research
Browse AI agent skills for product research, competitive analysis, customer discovery, and structured product decision support.
SKILL.md Source
# Nuwa · Skill Creation Engine (女娲 · Skill造人术)
> "The parts you can't write into a SKILL.md — that's your real moat." But the parts you CAN write are already powerful enough.
## Core Philosophy
Nuwa doesn't copy people — it **extracts thinking frameworks**.
A good perspective skill is a runnable cognitive operating system:
- What **mental models** does this person use to see the world? (lenses)
- What **decision heuristics** do they use to make judgments? (rules of thumb)
- How do they **express** themselves? (DNA)
- What do they **absolutely refuse** to do? (anti-patterns)
- What **can't** this skill do? (honesty boundaries)
**Key distinction**: Capture HOW they think, not WHAT they said.
---
## Execution Flow
### Phase 0: Clarify Requirements (30 seconds)
After receiving a name, confirm:
1. **Who is this person/topic**: Ensure correct understanding
2. **Focus direction** (optional): Full portrait vs. focused on one dimension?
3. **Purpose**: Thinking advisor? Decision reference? Role-play?
4. **New or update**: Does a skill for this person already exist?
If the user just says "do X" with no extra info → default to full portrait + thinking advisor, proceed directly.
### Phase 0.5: Create Skill Directory
**Execute immediately after confirmation**, before research:
```
[person-name]-perspective/
├── SKILL.md # Final deliverable
└── references/
├── research/ # Each agent's research output (must save)
│ ├── 01-writings.md # Writings & systematic thinking
│ ├── 02-conversations.md # Long conversations & improvisational thinking
│ ├── 03-expression-dna.md # Fragment expression & style DNA
│ ├── 04-external-views.md # External perspectives & criticism
│ ├── 05-decisions.md # Decision records & actions
│ └── 06-timeline.md # Person timeline
└── sources/ # Downloaded primary materials
├── books/
├── transcripts/
└── articles/
```
**Key rule**: Every subagent MUST save research results to its corresponding md file. Research without files is research that never happened. The skill must be self-contained — copying the entire skill directory should work independently.
---
### Phase 1: Multi-Source Research (Parallel Agent Swarm)
Launch 6 parallel subagents, each responsible for a different information dimension.
#### 6 Agent Assignments
| Agent | Search Target | Key Extractions | Output File |
|-------|--------------|-----------------|-------------|
| 1 Writings | Books, essays, papers, newsletters | Core arguments recurring ≥3 times = true belief, coined terms, reading lists | `01-writings.md` |
| 2 Conversations | Podcasts, long videos, AMAs, deep interviews | Responses under pressure, impromptu analogies, changed positions, refused questions | `02-conversations.md` |
| 3 Expression | Twitter/X, Weibo, short posts | High-frequency sentence patterns, controversial stances, humor style, public debates | `03-expression-dna.md` |
| 4 External | Others' analysis, book reviews, criticism, biographies | Externally observed patterns, criticism & controversies, peer comparisons | `04-external-views.md` |
| 5 Decisions | Major decisions, turning points, controversial actions | Decision context & logic, post-hoc reflections, say-do consistency | `05-decisions.md` |
| 6 Timeline | Birth/debut to present | Key milestones, thought turning points, **last 12 months** (prevent staleness) | `06-timeline.md` |
#### Hard Requirements for Each Agent
- Research results MUST be saved to `references/research/0X-xxx.md`
- Note source and credibility (primary > secondary > inference)
- Distinguish "they said" vs "others said about them" vs "I inferred"
- When contradictions are found, preserve them — don't smooth them over
#### Source Priority
| Source Type | What It Reveals | Weight |
|------------|----------------|--------|
| Their own writings | Systematic thinking | Highest |
| Long conversations/interviews | Improvisational thinking process | Highest |
| Actual decision records | Real behavior vs. claims | Highest |
| Social media | Expression style, instant reactions | Medium |
| Others' evaluations | External perspective, blind spots | Medium |
| Second-hand accounts | Reference but needs verification | Low |
#### Source Blocklist (Always Exclude)
For Chinese figures, exclude: Zhihu (知乎), WeChat public accounts (微信公众号), Baidu Baike/Zhidao. Only accept authoritative Chinese media: 36Kr, GeekPark, LatePost, Caixin, Yicai, Huxiu, SSPAI, etc.
#### Agent Failure Handling
- **Timeout/no results**: Don't wait, continue. Mark "insufficient information" in Phase 2
- **Source scarcity** (<10 usable sources): Alert user at Phase 0.5, lower expectations, increase honesty boundaries
- **Agent result conflicts**: Preserve contradictions — contradictions are valuable signals
**Key rule**: Better to generate an honest 60-point skill with clearly marked limitations than a seemingly perfect 90-point skill that fabricates information.
### Phase 1.5: Research Review Checkpoint
**After all agents complete, pause and display a research quality summary:**
```
┌──────────────────┬──────────┬──────────────────────────┐
│ Agent │ Sources │ Key Findings │
├──────────────────┼──────────┼──────────────────────────┤
│ 1 Writings │ 8 │ Core thesis: ... │
│ 2 Conversations │ 5 │ Position change: ... │
│ 3 Expression │ 120 │ High-freq: "skin in..." │
│ 4 External │ 6 │ Main criticism: ... │
│ 5 Decisions │ 4 │ Key decision: ... │
│ 6 Timeline │ Complete │ Latest: March 2026... │
├──────────────────┼──────────┼──────────────────────────┤
│ Contradictions │ 2 │ Agent1 says X, Agent4 Y │
│ Info gaps │ None │ │
└──────────────────┴──────────┴──────────────────────────┘
```
User confirms quality → proceed to Phase 2.
User wants more on some dimension → supplement before continuing.
---
### Phase 2: Framework Extraction (Synthesis)
#### 2.1 Mental Model Extraction (3-7)
Identification criteria:
- **Cross-domain recurrence**: Same framework appears in 2+ different domains → real mental model
- **Has coined terminology**: Named this thinking pattern → core belief
- **Predictive power**: Can predict their stance on new questions
Each model records: Name, one-line description, source evidence (≥2 scenarios), application method, limitations
#### 2.2 Decision Heuristics Extraction (5-10)
= Quick rules this person uses when making judgments. Expressible as "if X, then Y" with specific case support.
#### 2.3 Expression DNA Analysis
| Dimension | Extraction |
|-----------|-----------|
| Sentence preferences | Long/short, question/statement, analogy density |
| Vocabulary traits | High-frequency words, proprietary terms, taboo words |
| Rhythm | Conclusion-first or setup-first, transition style |
| Humor style | Sarcasm/self-deprecation/absurdist/dry/none |
| Certainty expression | "I'm not sure" type or "obviously" type |
| Citation habits | Who they cite, what type |
#### 2.4 Values & Anti-Patterns
- **Values**: 3-5 ranked core values
- **Anti-patterns**: Behaviors/thinking this person explicitly opposes
- **Contradictions & tensions**: Internal conflicts between values (source of depth)
#### 2.5 Intellectual Genealogy
Who influenced them → Them → Who they influenced → Position on the intellectual map
#### 2.6 Honesty Boundaries
Limitations that MUST be explicitly stated:
- Cannot predict reactions to entirely novel problems
- Cannot replace this person's creativity and intuition
- Public expression vs. private thoughts may differ
- Information cutoff at research date
---
### Phase 3: Skill Construction
Read `references/skill-template.md` for the standard template, fill in Phase 2 results.
Output: `SKILL.md` (main file) + research source index appended at the end.
---
### Phase 4: Quality Validation
After generating the skill, use a subagent for 3 independent tests:
#### 4.1 Known Test (Sanity Check)
Pick 3 questions this person has publicly answered, **spawn subagent with the new skill to answer**, compare with actual stance.
- Direction matches → model works
- Deviation → trace back and adjust mental model weights
#### 4.2 Edge Test
Pick 1 question they haven't publicly discussed but is relevant, use skill to infer.
- Expected: "Based on models X and Y, possibly... but uncertain"
- Should NOT be absolutely certain
#### 4.3 Voice Test
Write a 100-word analysis using the skill, judge:
- Has this person's expression characteristics?
- Not generic AI platitudes?
- Not a patchwork of original quotes?
#### 4.4 Pass Criteria
| Check | Pass | Fail Signal |
|-------|------|-------------|
| Mental model count | 3-7, each with source evidence | <3 or >10 |
| Each model's limitations | Clear failure conditions stated | Only upsides listed |
| Expression DNA recognition | Can identify who in 100 words | Reads like generic ChatGPT |
| Honesty boundaries | ≥3 specific limitations | Only "can't replace the person" |
| Internal tensions | ≥2 contradiction pairs | Views highly consistent (too fake) |
| Primary source ratio | >50% | Mainly second-hand accounts |
Pass → deliver. Fail → mark weak points, iterate back to Phase 2.
**Show validation results to user for confirmation before completion.**
---
## Updating Existing Skills
When user says "update X's skill" or "X has new developments":
1. Read existing SKILL.md, note last research date
2. Only launch Agent 2 (latest conversations) + Agent 5 (latest decisions) + Agent 6 (timeline update)
3. Compare new info with existing content — strengthen, update, or add
4. Update SKILL.md incrementally, don't rewrite entirely
---
## Taste Guidelines
### Good Skill vs Bad Skill
| Good Skill | Bad Skill |
|-----------|----------|
| Can handle new problems | Can only repeat old quotes |
| Has internal contradictions | All views highly consistent (fake) |
| Acknowledges uncertainty | Has answers for everything |
| 3-7 core models, deep and sharp | 20 vague "principles" |
| Expression has recognition | Reads like ChatGPT |
| Explicitly states limitations | Implies it can replace the person |
### Research Taste
1. **Primary > Secondary**: Their own words > others' accounts
2. **Long-form > Quotes**: A 3000-word essay reveals more thinking structure than 50 tweets
3. **Controversy > Consensus**: Most disputed views reveal the most uniqueness
4. **Change > Fixed**: Changed positions carry more information than consistent ones
5. **Behavior > Words**: Actual decisions > public statements
### Extraction Taste
1. **Less is more**: 3 deep mental models > 15 shallow principles
2. **Contradictions are features, not bugs**: Preserve internal tensions
3. **Don't beautify**: Blind spots and limitations are part of the personality
4. **Falsifiable**: Each mental model should be verifiable or refutable by specific cases
### Never Do
- Fabricate things this person never said
- Package generic wisdom as their "unique insight"
- Ignore negative evaluations and controversies
- Imply this skill equals the person themselves
- Force-generate when information is insufficient
---
## Special Scenarios
### Living Person vs Historical Figure
- **Living**: Watch for timeliness, mark cutoff date, suggest periodic updates
- **Historical**: More stable materials but possible biographical bias, cross-source verification
### Topic Skill vs Person Skill
Input is a topic (e.g., "value investing") not a person:
- Phase 1 searches for core practitioners and theorists of the topic
- Phase 2 extracts domain consensus + school-of-thought divergences
- Output centers on the topic, citing multiple person perspectives
---
## Final Note
Nuwa doesn't create people — it creates mirrors.
A good perspective skill lets you see your own problems through someone else's eyes. Not to imitate them, but to expand your own thinking boundaries.Related Skills
nuwa-world-api
Face search and deep research via the Nuwa World API — visual identity intelligence and knowledge synthesis from the open web.
---
name: article-factory-wechat
humanizer
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
find-skills
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
tavily-search
Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.
baidu-search
Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.
agent-autonomy-kit
Stop waiting for prompts. Keep working.
Meeting Prep
Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.
self-improvement
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.
botlearn-healthcheck
botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.
linkedin-cli
A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.
notebooklm
Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。