gh-linus-mcmanamey-unify-2-1-plugin/commands/prime-claude.md

name: prime-claude-md description: Distill CLAUDE.md to essentials, moving detailed knowledge into skills for on-demand loading. Reduces context pollution by 80-90%. args: [--analyze-only] | [--backup] | [--apply]

Prime CLAUDE.md

Distill your CLAUDE.md file to only essential information, moving detailed knowledge into skills.

Problem

Large CLAUDE.md files (400+ lines) are loaded into context for EVERY conversation:

• Wastes 5,000-15,000 tokens per conversation
• Reduces space for actual work
• Slows Claude's responses
• 80% of the content is rarely needed

Solution

Prime your CLAUDE.md:

1. Keep only critical architecture and coding standards
2. Move detailed knowledge into skills (loaded on-demand)
3. Reduce from 400+ lines to ~100 lines
4. Save 80-90% context per conversation

Usage

Analyze Current CLAUDE.md

/prime-claude-md --analyze-only

Shows what would be moved to skills without making changes.

Create Backup and Apply

/prime-claude-md --backup --apply

1. Backs up current CLAUDE.md to CLAUDE.md.backup
2. Creates supporting skills with detailed knowledge
3. Replaces CLAUDE.md with distilled version
4. Documents what was moved where

Just Apply (No Backup)

/prime-claude-md --apply

What Gets Distilled

Kept in CLAUDE.md (Essential)

• Critical architecture concepts (high-level only)
• Mandatory coding standards (line length, blank lines, decorators)
• Quality gates (syntax check, linting, formatting)
• Essential commands (2-3 most common)
• References to skills for details

Moved to Skills (Detailed Knowledge)

project-architecture skill:

• Detailed medallion architecture
• Pipeline execution flow
• Data source details
• Azure integration specifics
• Configuration management
• Testing architecture

project-commands skill:

• Complete make command reference
• All development workflows
• Azure operations
• Database operations
• Git operations
• Troubleshooting commands

pyspark-patterns skill:

• TableUtilities method documentation
• ETL class pattern details
• Logging standards
• DataFrame operation patterns
• JDBC connection patterns
• Performance tips

Results

Before Priming:

• CLAUDE.md: 420 lines
• Context cost: ~12,000 tokens per conversation
• Skills: 0
• Knowledge: Always loaded

After Priming:

• CLAUDE.md: ~100 lines (76% reduction)
• Context cost: ~2,000 tokens per conversation (83% savings)
• Skills: 3 specialized skills
• Knowledge: Loaded only when needed

Example Distilled CLAUDE.md

# CLAUDE.md

**CRITICAL**: READ `.claude/rules/python_rules.md`

## Architecture
Medallion: Bronze → Silver → Gold
Core: `session_optimiser.py` (SparkOptimiser, NotebookLogger, TableUtilities)

## Essential Commands
python3 -m py_compile <file>  # Must run
ruff check python_files/       # Must pass
make run_all                   # Full pipeline

## Coding Standards
- Line length: 240 chars
- No blank lines in functions
- Use @synapse_error_print_handler
- Use logger (not print)

## Skills Available
- project-architecture: Detailed architecture
- project-commands: Complete command reference
- pyspark-patterns: PySpark best practices

Benefits

1. Faster conversations: Less context overhead
2. Better responses: More room for actual work
3. On-demand knowledge: Load only what you need
4. Maintainable: Easier to update focused skills
5. Reusable pattern: Apply to any repository

Applying to Other Repositories

This command is repository-agnostic. To use on another repo:

1. Run /prime-claude-md --analyze-only to see what you have
2. Command will identify:
   • Architectural concepts
   • Command references
   • Coding standards
   • Configuration details
3. Creates appropriate skills based on content
4. Run /prime-claude-md --apply when ready

Files Created

.claude/
├── CLAUDE.md                          # Distilled (100 lines)
├── CLAUDE.md.backup                   # Original (if --backup used)
└── skills/
    ├── project-architecture/
    │   └── skill.md                   # Architecture details
    ├── project-commands/
    │   └── skill.md                   # Command reference
    └── pyspark-patterns/              # (project-specific)
        └── skill.md                   # Code patterns

Philosophy

CLAUDE.md should answer: "What's special about this repo?"

Skills should answer: "How do I do X in detail?"

Task Execution

I will:

1. Read current CLAUDE.md (both project and global if exists)
2. Analyze content and categorize
3. Create distilled CLAUDE.md (essential only)
4. Create supporting skills with detailed knowledge
5. If --backup: Save CLAUDE.md.backup
6. If --apply: Replace CLAUDE.md with distilled version
7. Generate summary report of changes

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Current Project: Unify Data Migration (PySpark/Azure Synapse)

Let me analyze your CLAUDE.md and create the distilled version with supporting skills.