Claude code mastery
Design better agents, skills and hooks for Claude Code, checking the current spec instead of guessing at fields.From its SKILL.md
npx -y skills add ToruAI/toru-claude-agents --skill claude-code-masteryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
4.5 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Claude Code Mastery - Building Better AI Systems
Use the cc-docs skill to read the official Claude Code documentation before you design
anything against it — the spec moves, and this file is a map, not a substitute for it.
Use this knowledge to continuously improve how you work.
Core Capabilities
Subagents
Location: ~/.claude/agents/ (user) or .claude/agents/ (project)
Key fields:
---
name: agent-name
description: When Claude should delegate here
tools: Read, Grep, Glob, Bash, Edit, Write
model: sonnet | opus | haiku | inherit
permissionMode: default | acceptEdits | bypassPermissions
skills: skill-1, skill-2
hooks:
PreToolUse: [...]
PostToolUse: [...]
---
System prompt content here...
Use subagents when:
- Task needs isolated context
- Different tools/permissions needed
- Specialized behavior required
Skills
Location: ~/.claude/skills/ (user) or .claude/skills/ (project)
Structure:
skill-name/
├── SKILL.md # Required - main instructions
├── reference.md # Optional - detailed docs
└── scripts/ # Optional - utilities
Key fields:
---
name: skill-name
description: When to apply this skill (triggers auto-loading)
allowed-tools: Read, Grep, Glob # Optional tool restriction
context: fork # Optional - run in subagent
---
Instructions here...
Use skills when:
- Knowledge should auto-apply based on task
- Pattern repeats across projects
- Want to inject expertise without delegation
Hooks
Location: .claude/settings.json or subagent frontmatter
Events:
PreToolUse- Before tool executes (can block)PostToolUse- After tool executesSubagentStart- When subagent beginsSubagentStop- When subagent completesSessionStart- When session begins
Example:
{
"hooks": {
"PostToolUse": [{
"matcher": "Edit|Write",
"hooks": [{
"type": "command",
"command": "./scripts/auto-lint.sh"
}]
}]
}
}
Use hooks when:
- Deterministic action needed (not AI judgment)
- Automation on every occurrence
- Validation before allowing operations
MCP Servers
Configuration: ~/.claude.json or .mcp.json
Access external tools:
- megg (memory)
- shadcn (UI components)
- perplexity (research)
- Custom servers
Improvement Patterns
Pattern: Repeated Context Loading
Problem: Same context loaded every session Solution: Create a skill that auto-applies
---
name: project-context
description: Apply when working on [project]. Auto-loads conventions.
---
Pattern: Manual Validation
Problem: Manually checking things before commit Solution: Create PreToolUse hook
{
"hooks": {
"PreToolUse": [{
"matcher": "Bash(git commit:*)",
"hooks": [{"type": "command", "command": "./scripts/pre-commit-check.sh"}]
}]
}
}
Pattern: Complex Delegation
Problem: Unclear when to use which agent Solution: Improve agent descriptions, add proactive triggers
description: Use proactively when [specific trigger]. Handles [specific task].
Pattern: Lost Knowledge
Problem: Decisions forgotten between sessions Solution: megg_remember after every significant decision
Documentation Reference
Fetch these with the cc-docs skill rather than trusting a remembered field list:
| Topic | URL |
|---|---|
| Subagents | https://code.claude.com/docs/en/sub-agents |
| Skills | https://code.claude.com/docs/en/skills |
| Hooks | https://code.claude.com/docs/en/hooks-guide |
| MCP | https://code.claude.com/docs/en/mcp |
| Headless mode | https://code.claude.com/docs/en/headless |
| Settings | https://code.claude.com/docs/en/settings |
| CLI reference | https://code.claude.com/docs/en/cli-reference |
Self-Improvement Checklist
When improving workflows:
- Identify the friction point
- Check docs for existing solution
- Choose right tool (skill vs hook vs subagent)
- Implement minimal version
- Test it works
- Document in megg
- Consider if others need it (project vs user scope)
Anti-Patterns
- Over-engineering: Don't create skills for one-time tasks
- Premature automation: Prove manual workflow first
- Isolated improvements: Log all changes in megg
- Ignoring scope: User skills for personal, project for team
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most context ai engineering skills give in ~1.1k tokens
Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06
- Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
- Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
- Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
- Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
- Use the least powerful model capable of the taskin 33 of 1328, across 26 files
- Create a TodoWrite list for all tasksin 32 of 1328, across 22 files
- Perform a task review after each implementationin 31 of 1328, across 24 files
- Extract all tasks and context from the planin 29 of 1328, across 20 files
- Provide full task text to subagentsin 28 of 1328, across 20 files
- Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
- Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
- Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files
Said here and by no other author read
- use subagents for isolated context
- use hooks for deterministic automation
- use megg to remember significant decisions
- prove manual workflows before automating
- log all changes in megg
- use user scope for personal tasks
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.