coding-custom（编码定制）

When to Use

User has coding style preferences, stack decisions, or patterns they want remembered. Agent learns ONLY from explicit corrections and confirmations, never from observation.

Architecture

Memory lives in ~/coding/ with tiered structure. See memory-template.md for setup.

~/coding/
├── memory.md      # Active preferences (≤100 lines)
└── history.md     # Archived old preferences

Quick Reference

Data Storage

All data stored in ~/coding/. Create on first use:

mkdir -p ~/coding

Scope

This skill ONLY:

• Learns from explicit user corrections ("I prefer X over Y")
• Stores preferences in local files (~/coding/)
• Applies stored preferences to code output

This skill NEVER:

• Reads project files to infer preferences
• Observes coding patterns without consent
• Makes network requests
• Reads files outside ~/coding/
• Modifies its own SKILL.md

Core Rules

1. Learn from Explicit Feedback Only

• User corrects output → ask: "Should I remember this preference?"
• User confirms → add to ~/coding/memory.md
• Never infer from silence or observation

2. Confirmation Required

No preference is stored without explicit user confirmation:

• "Actually, I prefer X" → "Should I remember: prefer X?"
• User says yes → store
• User says no → don't store, don't ask again

3. Ultra-Compact Format

Keep each entry 5 words max:

• python: prefer 3.11+
• naming: snake_case for files
• tests: colocated, not separate folder

4. Category Organization

Group by type (see dimensions.md):

• Stack — frameworks, databases, tools
• Style — naming, formatting, comments
• Structure — folders, tests, configs
• Never — explicitly rejected patterns

5. Memory Limits

• memory.md ≤100 lines
• When full → archive old patterns to history.md
• Merge similar entries: "no Prettier" + "no ESLint" → "minimal tooling"

6. On Session Start

1. Load ~/coding/memory.md if exists
2. Apply stored preferences to responses
3. If no file exists, start with no assumptions

7. Query Support

User can ask:

• "Show my coding preferences" → display memory.md
• "Forget X" → remove from memory
• "What do you know about my Python style?" → show relevant entries

Common Traps

• Adding preferences without confirmation → user loses trust
• Inferring from project structure → privacy violation
• Exceeding 100 lines → context bloat
• Vague entries ("good code") → useless, be specific

Security & Privacy

Data that stays local:

• All preferences stored in ~/coding/
• No telemetry or analytics

This skill does NOT:

• Send data externally
• Access files outside ~/coding/
• Observe without explicit user input

Feedback

• If useful: clawhub star coding
• Stay updated: clawhub sync