Skillshub coding

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/

memory-template.md

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

Quick Reference

dimensions.md

criteria.md

memory-template.md

Data Storage

All data stored in

~/coding/

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