ScriptsJul 18, 2026·4 min read

Nuwa Skill — Distill Anyone's Thinking into an AI Skill

An open-source tool that extracts mental models, decision heuristics, and communication patterns from any person's content, then packages them as reusable AI agent skills.

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Agent surface
Any MCP/CLI agent
Kind
Skill
Install
Single
Trust
Trust: Established
Entrypoint
Nuwa Skill
Review-first command
npx -y tokrepo@latest install c8684f62-82c5-11f1-9bc6-00163e2b0d79 --target codex

Dry-run first, confirm the writes, then run this command.

Introduction

Nuwa Skill is an open-source framework for extracting structured thinking patterns from a person's written or spoken content and packaging them as reusable AI agent skills. It targets anyone who wants to capture expertise — their own or someone else's — in a format that LLM agents can directly consume and apply.

What Nuwa Skill Does

  • Analyzes a corpus of content (articles, transcripts, posts) to identify recurring mental models and decision heuristics
  • Extracts communication patterns including tone, structure, and rhetorical preferences
  • Generates a structured skill file that encodes the person's reasoning style as agent instructions
  • Supports multiple input formats including text files, URLs, and transcript exports
  • Produces skills compatible with Claude Code, Cursor, and other agent harnesses that accept markdown-based skill definitions

Architecture Overview

Nuwa Skill operates as a multi-stage pipeline. The ingestion layer normalizes diverse input formats into plain text chunks. An analysis stage uses LLM calls to identify patterns across the corpus — recurring frameworks, decision criteria, writing conventions, and domain-specific vocabulary. A synthesis stage consolidates these patterns into a coherent skill definition with structured sections for context, triggers, instructions, and examples. The final output is a markdown file conforming to common agent skill formats. The pipeline is implemented in Python and uses configurable LLM backends for the analysis and synthesis steps.

Self-Hosting & Configuration

  • Clone the repository and install dependencies with pip; runs on any system with Python 3.10+
  • Configure your preferred LLM provider (OpenAI, Anthropic, or compatible APIs) via environment variables
  • Point the tool at a directory of source content or provide URLs for web-based content
  • Adjust extraction parameters such as chunk size and analysis depth in the configuration file
  • Output skill files can be placed directly into .claude/skills/ or equivalent directories for immediate use

Key Features

  • Content-agnostic extraction works with blog posts, podcast transcripts, forum replies, and long-form writing
  • Produces portable skill definitions that work across multiple agent platforms
  • Iterative refinement mode lets you review and adjust extracted patterns before finalizing
  • Supports batch processing of large content libraries for prolific authors
  • Open architecture allows adding custom analysis modules for domain-specific pattern extraction

Comparison with Similar Tools

  • Custom GPTs (OpenAI) — require manual prompt writing; Nuwa Skill automates pattern extraction from existing content
  • Claude Projects — let you upload reference docs for context; Nuwa Skill goes further by distilling actionable instructions from the content
  • Fabric (Daniel Miessler) — provides pre-built prompt patterns; Nuwa Skill generates personalized patterns from individual content
  • MemGPT / Letta — focus on long-term memory for agents; Nuwa Skill focuses on capturing reasoning style rather than facts
  • Prompt engineering by hand — time-consuming and inconsistent; Nuwa Skill systematizes the extraction process

FAQ

Q: What kind of content works best as input? A: Content where the author explains their reasoning — blog posts with opinions, podcast transcripts with discussions, and advisory writing — yields the richest skill extractions.

Q: Does it work with non-English content? A: Yes, as long as the underlying LLM supports the language. The extraction pipeline is language-agnostic; quality depends on the LLM's proficiency in that language.

Q: How is this different from just uploading documents to an AI chat? A: Uploading documents provides raw context. Nuwa Skill distills that context into structured instructions — triggers, decision rules, and output formats — that an agent can follow without re-reading the source material.

Q: Can I merge skills from multiple people? A: The tool generates one skill per corpus. You can run it on separate content sets and use multiple skills simultaneously in agents that support skill stacking.

Sources

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