Coding
Coding style memory that adapts to your preferences, conventions, and patterns for consistent coding.
Best use case
Coding is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Coding style memory that adapts to your preferences, conventions, and patterns for consistent coding.
Teams using Coding should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/coding/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Coding Compares
| Feature / Agent | Coding | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Coding style memory that adapts to your preferences, conventions, and patterns for consistent coding.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
## 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:
```bash
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`Related Skills
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