184 lines
4.9 KiB
Markdown
184 lines
4.9 KiB
Markdown
---
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name: prime-claude-md
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description: Distill CLAUDE.md to essentials, moving detailed knowledge into skills for on-demand loading. Reduces context pollution by 80-90%.
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args: [--analyze-only] | [--backup] | [--apply]
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---
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# Prime CLAUDE.md
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Distill your CLAUDE.md file to only essential information, moving detailed knowledge into skills.
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## Problem
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Large CLAUDE.md files (400+ lines) are loaded into context for EVERY conversation:
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- Wastes 5,000-15,000 tokens per conversation
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- Reduces space for actual work
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- Slows Claude's responses
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- 80% of the content is rarely needed
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## Solution
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**Prime your CLAUDE.md**:
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1. Keep only critical architecture and coding standards
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2. Move detailed knowledge into skills (loaded on-demand)
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3. Reduce from 400+ lines to ~100 lines
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4. Save 80-90% context per conversation
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## Usage
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### Analyze Current CLAUDE.md
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```bash
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/prime-claude-md --analyze-only
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```
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Shows what would be moved to skills without making changes.
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### Create Backup and Apply
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```bash
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/prime-claude-md --backup --apply
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```
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1. Backs up current CLAUDE.md to CLAUDE.md.backup
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2. Creates supporting skills with detailed knowledge
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3. Replaces CLAUDE.md with distilled version
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4. Documents what was moved where
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### Just Apply (No Backup)
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```bash
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/prime-claude-md --apply
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```
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## What Gets Distilled
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### Kept in CLAUDE.md (Essential)
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- Critical architecture concepts (high-level only)
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- Mandatory coding standards (line length, blank lines, decorators)
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- Quality gates (syntax check, linting, formatting)
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- Essential commands (2-3 most common)
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- References to skills for details
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### Moved to Skills (Detailed Knowledge)
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**project-architecture** skill:
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- Detailed medallion architecture
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- Pipeline execution flow
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- Data source details
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- Azure integration specifics
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- Configuration management
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- Testing architecture
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**project-commands** skill:
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- Complete make command reference
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- All development workflows
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- Azure operations
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- Database operations
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- Git operations
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- Troubleshooting commands
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**pyspark-patterns** skill:
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- TableUtilities method documentation
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- ETL class pattern details
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- Logging standards
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- DataFrame operation patterns
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- JDBC connection patterns
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- Performance tips
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## Results
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**Before Priming**:
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- CLAUDE.md: 420 lines
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- Context cost: ~12,000 tokens per conversation
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- Skills: 0
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- Knowledge: Always loaded
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**After Priming**:
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- CLAUDE.md: ~100 lines (76% reduction)
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- Context cost: ~2,000 tokens per conversation (83% savings)
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- Skills: 3 specialized skills
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- Knowledge: Loaded only when needed
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## Example Distilled CLAUDE.md
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```markdown
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# CLAUDE.md
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**CRITICAL**: READ `.claude/rules/python_rules.md`
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## Architecture
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Medallion: Bronze → Silver → Gold
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Core: `session_optimiser.py` (SparkOptimiser, NotebookLogger, TableUtilities)
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## Essential Commands
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python3 -m py_compile <file> # Must run
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ruff check python_files/ # Must pass
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make run_all # Full pipeline
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## Coding Standards
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- Line length: 240 chars
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- No blank lines in functions
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- Use @synapse_error_print_handler
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- Use logger (not print)
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## Skills Available
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- project-architecture: Detailed architecture
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- project-commands: Complete command reference
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- pyspark-patterns: PySpark best practices
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```
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## Benefits
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1. **Faster conversations**: Less context overhead
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2. **Better responses**: More room for actual work
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3. **On-demand knowledge**: Load only what you need
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4. **Maintainable**: Easier to update focused skills
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5. **Reusable pattern**: Apply to any repository
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## Applying to Other Repositories
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This command is repository-agnostic. To use on another repo:
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1. Run `/prime-claude-md --analyze-only` to see what you have
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2. Command will identify:
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- Architectural concepts
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- Command references
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- Coding standards
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- Configuration details
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3. Creates appropriate skills based on content
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4. Run `/prime-claude-md --apply` when ready
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## Files Created
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```
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.claude/
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├── CLAUDE.md # Distilled (100 lines)
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├── CLAUDE.md.backup # Original (if --backup used)
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└── skills/
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├── project-architecture/
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│ └── skill.md # Architecture details
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├── project-commands/
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│ └── skill.md # Command reference
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└── pyspark-patterns/ # (project-specific)
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└── skill.md # Code patterns
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```
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## Philosophy
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**CLAUDE.md should answer**: "What's special about this repo?"
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**Skills should answer**: "How do I do X in detail?"
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## Task Execution
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I will:
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1. Read current CLAUDE.md (both project and global if exists)
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2. Analyze content and categorize
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3. Create distilled CLAUDE.md (essential only)
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4. Create supporting skills with detailed knowledge
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5. If --backup: Save CLAUDE.md.backup
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6. If --apply: Replace CLAUDE.md with distilled version
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7. Generate summary report of changes
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---
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**Current Project**: Unify Data Migration (PySpark/Azure Synapse)
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Let me analyze your CLAUDE.md and create the distilled version with supporting skills.
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