context-extractor

name	context-extractor
description	Analyze a project and extract conventions, patterns, and context into a CLAUDE.md file. Works for any project type — code repos, presentation collections, research corpora, documentation projects. Trigger on "extract conventions", "analyze project patterns", "generate CLAUDE.md", "what are the conventions", or /conventions.

Context Extractor

Analyze the current project and draft a CLAUDE.md capturing its conventions, patterns, and context. Works for ANY project type, not just code.

Workflow

Step 1: Detect Project Type

Scan the project root to determine what kind of project this is:

Signals	Project Type
package.json, Cargo.toml, pyproject.toml, go.mod, pubspec.yaml	Code repository
.github/workflows/, Jenkinsfile, .gitlab-ci.yml	CI/CD pipeline
*.pptx, *.key, slides/	Presentation collection
*.md collection, docs/, wiki/	Documentation project
data/, notebooks/, *.ipynb	Data/research project
Mixed or unclear	General project

A project may be multiple types. Identify the primary and secondary types.

Step 2: Scan for Conventions

Based on detected type(s), scan using the appropriate checklist:

For all project types:

• File/directory organization and naming patterns
• Existing README.md, CONTRIBUTING.md, CLAUDE.md content
• Git commit message style (last 20 commits)
• Any .editorconfig, .prettierrc, or formatting configs

For code repositories (add to above):

• Build system and commands (from package.json scripts, Makefile, etc.)
• Language conventions: naming style, import patterns, error handling (sample 5-10 source files)
• Test framework, test file naming, test patterns
• CI/CD quality gates
• Linting/formatting configuration
• Non-obvious: .env.example, docker-compose, special scripts, gotchas

For presentation projects:

• Slide structure patterns (title slides, section dividers, etc.)
• Branding: colors, fonts, logos used
• Template files
• Naming conventions for slide decks

For documentation projects:

• Document structure (headings, sections)
• Citation/reference style
• Metadata/frontmatter patterns
• File naming conventions

For data/research projects:

• Notebook structure patterns
• Data pipeline conventions
• Naming for datasets, experiments
• Environment setup

Step 3: Draft CLAUDE.md

Use the template at references/templates/claude-md-template.md as a starting point. Fill in discovered conventions.

Rules:

• Keep it concise — only include what Claude can't infer from reading the code/files
• Use imperative style ("Run X before committing", not "The team prefers to run X")
• Focus on non-obvious things that would cause mistakes
• Include build/test/run commands prominently

Step 4: Present to User

• If CLAUDE.md already exists: present proposed additions as a diff. NEVER remove existing user content.
• If no CLAUDE.md exists: present the full draft.
• NEVER apply without explicit user approval.

Update Mode

When called on a project that already has a good CLAUDE.md:

1. Run the analysis
2. Compare findings against existing CLAUDE.md
3. Propose ADDITIONS only (new conventions not yet documented)
4. Present as individual proposals the user can accept/reject