Are the generated skills portable between projects?

Yes, the primary goal is portability. The extractor removes project-specific hardcoded values like local paths or credentials so the skill can be installed anywhere.

What files are generated during the extraction process?

It creates a dedicated directory containing a SKILL.md file (with frontmatter), a human-readable README.md, and a reference folder with concrete code examples.

What is the main purpose of the /si:extract command?

It automates the creation of reusable Claude Code skills by turning specific debugging solutions or recurring coding patterns into standalone documentation.

How does it find the information needed to create a skill?

The tool scans your project's local auto-memory directory for related entries and combines that with user-provided descriptions to synthesize the skill content.

When is a pattern eligible for skill extraction?

A pattern should be extracted if it is recurring across projects, required non-obvious debugging to discover, is broadly applicable, or involves a complex multi-step fix.

Pattern Extractor & Skill Generator

Name: Pattern Extractor & Skill Generator
Author: zhangzhang-111-i

byzhangzhang-111-i

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Productividad y Flujo de Trabajo

Transforms recurring debugging solutions and development patterns into reusable, portable Claude Code skills.

The Extract skill automates the process of capturing institutional knowledge by converting one-off solutions into structured, portable documentation. By searching through project history and auto-memory, it identifies non-obvious patterns—such as complex environment fixes or specific workflow sequences—and packages them into a standardized SKILL.md format. This allows engineering teams to build a library of self-improving agents that can be easily shared across different projects, ensuring that hard-won lessons are never lost and remain instantly actionable for any developer.

Características Principales

010 GitHub stars

02Automated pattern identification from project memory and terminal history

03Supports dry-run mode to preview skill structures before file generation

04Generates standardized SKILL.md files with YAML frontmatter and quality gates

05Interactive extraction workflow to define scope, naming, and edge cases

06Creates comprehensive documentation including READMEs and usage examples

Casos de Uso

01Standardizing a custom API client regeneration workflow across multiple repositories

02Converting a multi-step Docker configuration fix for specific hardware into a reusable team resource

03Documenting non-obvious debugging solutions found during complex legacy code migrations

Características Principales

010 GitHub stars

02Automated pattern identification from project memory and terminal history

03Supports dry-run mode to preview skill structures before file generation

04Generates standardized SKILL.md files with YAML frontmatter and quality gates

05Interactive extraction workflow to define scope, naming, and edge cases

06Creates comprehensive documentation including READMEs and usage examples

Casos de Uso

01Standardizing a custom API client regeneration workflow across multiple repositories

02Converting a multi-step Docker configuration fix for specific hardware into a reusable team resource

03Documenting non-obvious debugging solutions found during complex legacy code migrations