---
name: ai-agent-code-learning
classification: capability
classification-reason: Highly likely to be subsumed by model's native capabilities
deprecation-risk: high
description: |
  Antigravity Platform learning — configure and optimize Antigravity Platform settings, tips, and workflows.
  Triggers: learn, setup, ai-agent code, optimize, 학습, 설정, 최적화.
argument-hint: "[learn|setup|upgrade] [level]"
agent: ai-agent-code-guide
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - Bash
  - AskUserQuestion
user-invocable: true
imports:
  - ${PLUGIN_ROOT}/templates/shared/naming-conventions.md
next-skill: null
pdca-phase: null
task-template: "[Learn] Antigravity Platform {level}"
hooks:
  Stop:
    - type: command
      command: "node ${HMCMKIT_PLUGIN_ROOT}/scripts/learning-stop.js"
      timeout: 10000
---

# Antigravity Platform Learning Skill

> Master Antigravity Platform configuration and optimization

## Actions

| Action | Description | Example |
|--------|-------------|---------|
| `learn` | Start learning guide | `/ai-agent-code-learning learn 1` |
| `setup` | Auto-generate settings | `/ai-agent-code-learning setup` |
| `upgrade` | Latest features guide | `/ai-agent-code-learning upgrade` |

### learn [level]

Learning content by level:
- **Level 1**: Basics - Writing agents.md, Using Plan Mode
- **Level 2**: Automation - Commands, Hooks, Permission management
- **Level 3**: Specialization - Agents, Skills, MCP integration
- **Level 4**: Team Optimization - GitHub Action, Team rule standardization
- **Level 5**: PDCA Methodology - hmcmkit methodology learning

### setup

Auto-generate appropriate settings after analyzing current project:
1. Analyze/generate agents.md
2. Check .ai-agent/ folder structure
3. Suggest required configuration files

### upgrade

Guide to latest Antigravity Platform features and best practices.

## Learning Levels

### Level 1: Basics (15 min)

```markdown
## What is agents.md?

A shared knowledge repository for the team. When AI Agent makes mistakes,
add rules to prevent the same mistakes from recurring.

## Example

# Development Workflow

## Package Management
- **Always use `pnpm`** (`npm`, `yarn` prohibited)

## Coding Conventions
- Prefer `type`, avoid `interface`
- **Never use `enum`** → Use string literal unions

## Prohibited
- ❌ No console.log (use logger)
- ❌ No any type
```

### Level 2: Automation (30 min)

```markdown
## What are Slash Commands?

Execute repetitive daily tasks with `/command-name`.

## Command Location

.ai-agent/commands/{command-name}.md

## PostToolUse Hook

Auto-formatting after code modification:

// .ai-agent/settings.local.json
{
  "hooks": {
    "PostToolUse": [{
      "matcher": "Write|Edit",
      "hooks": [{
        "type": "command",
        "command": "pnpm format || true"
      }]
    }]
  }
}
```

### Level 3: Specialization (45 min)

```markdown
## What are Sub-agents?

AI agents specialized for specific tasks.

## What are Skills?

Domain-specific expert context. AI Agent auto-references when working on related tasks.

## MCP Integration

Connect external tools (Slack, GitHub, Jira, etc.) via .mcp.json.
```

### Level 4: Team Optimization (1 hour)

```markdown
## PR Automation with GitHub Action

Mention @ai-agent in PR comments to auto-update documentation.

## Team Rule Standardization

1. Manage agents.md with Git
2. Add rules during PR review
3. Gradually accumulate team knowledge

## Agent Teams (v1.5.1)

Parallel PDCA execution with multiple AI agents working simultaneously.

Requirements:
  HMCMKIT_EXPERIMENTAL_AGENT_TEAMS=1

Usage:
  /pdca team {feature}     Start team mode
  /pdca team status        Check teammate progress
  /pdca team cleanup       End team session

Team composition by level:
  Dynamic:    2 teammates (developer, qa)
  Enterprise: 4 teammates (architect, developer, qa, reviewer)
```

### Level 5: PDCA Methodology

```markdown
## What is PDCA?

Document-driven development methodology.

Plan → Design → Do → Check → Act

## Folder Structure

docs/
├── 01-plan/      # Planning
├── 02-design/    # Design
├── 03-analysis/  # Analysis
└── 04-report/    # Reports

## Learn More

Use /pdca skill to learn PDCA methodology.
```

### Level 6: Advanced Features (v1.5.1)

```markdown
## Output Styles

Customize how AI Agent responds based on your project level.

Available styles:
  hmcmkit-learning     Best for beginners (learning points, TODO markers)
  hmcmkit-pdca-guide   Best for PDCA workflows (status badges, checklists)
  hmcmkit-enterprise   Best for architects (tradeoff analysis, cost impact)

Usage:
  /output-style              Select interactively
  /output-style hmcmkit-learning  Apply directly

Auto-recommendation:
  Starter → hmcmkit-learning
  Dynamic → hmcmkit-pdca-guide
  Enterprise → hmcmkit-enterprise

## Agent Memory

All hmcmkit agents automatically remember context across sessions.
No configuration needed.

Memory scopes:
  project   9 agents remember per-project context (.ai-agent/agent-memory/)
  user      2 agents remember cross-project learning (~/.ai-agent/agent-memory/)

Agents with user-scope memory:
  starter-guide     Remembers your learning progress across projects
  pipeline-guide    Remembers your pipeline preferences globally

## Agent Teams

Parallel PDCA execution for Dynamic and Enterprise projects.
See Level 4 for details.
```

## Output Format

```
📚 Antigravity Platform Learning Complete!

**Current Level**: {level}
**Learned**: {summary}

🎯 Next Steps:
- Continue learning with /ai-agent-code-learning learn {next_level}
- Auto-generate settings with /ai-agent-code-learning setup
- Check latest trends with /ai-agent-code-learning upgrade
```

## Current Settings Analysis

Files to analyze:
- agents.md (root)
- .ai-agent/settings.local.json
- .ai-agent/commands/
- .ai-agent/agents/
- .ai-agent/skills/
- .mcp.json

## Skills 2.0 Hot Reload (CC 2.1.0+)

CC 2.1.0+ supports hot reload for skill changes. No session restart needed.

### Hot Reload Scope
- SKILL.md body changes: Instant reflection
- Frontmatter field changes: Instant reflection
- New skill additions: Instant reflection

### Development Workflow
1. Edit SKILL.md content and save
2. Next slash invoke reflects changes immediately
3. Use `/reload-plugins` for forced refresh

### Tips
- Test with `/eval run [skill-name]` after changes
- Use `classification` frontmatter to categorize skills
- Monitor with `/loop 5m /pdca status` for ongoing work