npx claudepluginhub melodic-software/claude-code-plugins --plugin tacThis skill is limited to using the following tools:
Create a minimum viable agentic layer structure for a project.
Guides setup of minimal agentic layer: specs dir, Claude chore/implement commands, Python agent module, and gateway script for bootstrapping agentic coding in projects.
Scaffolds .agents/ folder structure for AI-first development, including session tracking, task management, coding standards, ADRs, security checklists, and configs for .claude, .codex, .cursor. Use when starting AI-assisted projects.
Guides creation of Claude Code agents via 5 phases: analyze requirements and type, design architecture with patterns/skills, create files/frontmatter, validate, refine iteratively.
Share bugs, ideas, or general feedback.
Create a minimum viable agentic layer structure for a project.
$ARGUMENTS: Project name or target directoryYou are scaffolding a minimum viable agentic layer for a project.
mkdir -p specs
mkdir -p .claude/commands
mkdir -p adws/adw_modules
mkdir -p agents
Create .claude/commands/chore.md:
# Chore Planning
Create a detailed implementation plan for this chore task.
## Task Description
$ARGUMENTS
## Instructions
1. Analyze the task requirements
2. Identify files to modify
3. Create step-by-step implementation plan
4. Define validation criteria
## Output
Create a spec file at: `specs/chore-{timestamp}-{name}.md`
Include:
- Task overview
- Files to modify
- Implementation steps
- Validation checklist
Create .claude/commands/implement.md:
# Implementation
Implement the plan provided.
## Plan File
$ARGUMENTS
## Instructions
1. Read the plan file completely
2. Implement each step in order
3. Validate against criteria
4. Report changes
## Output
Report with:
- Changes made (git diff --stat)
- Validation results
- Any issues encountered
Create adws/adw_modules/__init__.py:
"""
ADW Modules - Core agent execution utilities.
To implement:
- agent.py: Claude Code subprocess execution
- data_types.py: Pydantic request/response models
"""
Create adws/README.md:
# AI Developer Workflows
This directory contains the agentic layer for this project.
## Structure
- `adw_modules/`: Core execution modules
- `adw_*.py`: Workflow scripts
## Getting Started
1. Implement `adw_modules/agent.py` with Claude Code execution
2. Create gateway scripts (e.g., `adw_prompt.py`)
3. Build composed workflows (e.g., `adw_chore_implement.py`)
## Usage
Run workflows from project root:
```bash
python adws/adw_prompt.py "Your prompt here"
Report created structure:
## Agentic Layer Scaffolded
**Project:** {name}
**Date:** {today}
### Created Directories
- specs/
- .claude/commands/
- adws/adw_modules/
- agents/
### Created Files
- .claude/commands/chore.md
- .claude/commands/implement.md
- adws/adw_modules/__init__.py
- adws/README.md
### Next Steps
1. Implement `adws/adw_modules/agent.py`:
- Claude Code subprocess execution
- Request/response data models
- Output file handling
2. Create gateway script `adws/adw_prompt.py`:
- CLI interface with click
- Unique ID generation
- Rich console output
3. Create composed workflow `adws/adw_chore_implement.py`:
- Execute /chore to generate plan
- Execute /implement with plan
### Time to Production
Estimated 5-8 hours to complete MVP