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

Topic	File
Categories of preferences	`dimensions.md`
When to add preferences	`criteria.md`
Memory templates	`memory-template.md`

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

Load ~/coding/memory.md if exists
Apply stored preferences to responses
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

Coding