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agentic-layer-audit

Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.

SKILL.md

Full skill instructions

Agentic Layer Audit Skill

Evaluate a codebase's agentic layer maturity and identify investment opportunities.

When to Use

  • Assessing current agentic layer coverage
  • Identifying gaps in automation
  • Planning agentic layer investments
  • Measuring progress toward 50%+ agentic time

Core Concept

"Am I working on the agentic layer or am I working on the application layer?"

This skill helps answer that question by auditing what exists.

Audit Checklist

1. Commands Directory

Check for .claude/​commands/ or equivalent:

Look for:
- chore.md      # Chore planning template
- bug.md        # Bug fix template
- feature.md    # Feature planning template
- implement.md  # Implementation HOP
- test.md       # Test execution template
- review.md     # Review template

2. Specs Directory

Check for specs/ or equivalent:

Look for:
- Issue-based specs (issue-*.md)
- Generated plans (chore-*.md, feature-*.md)
- Deep specs (complex multi-file architectures)

3. ADW Directory

Check for adws/ or equivalent:

Look for:
- adw_modules/​agent.py  # Core agent execution
- Gateway scripts (adw_prompt.py, adw_slash_command.py)
- Composed workflows (adw_*_*.py)
- Triggers (trigger_*.py)

4. Hooks Directory

Check for .claude/​hooks/ or equivalent:

Look for:
- pre_tool_use hooks
- post_tool_use hooks
- user_prompt_submit hooks

5. Agent Output Directory

Check for agents/ or equivalent:

Look for:
- ADW ID directories
- State files (adw_state.json)
- Output files (cc_*.jsonl, cc_*.json)

6. Worktree Support

Check for trees/ or equivalent:

Look for:
- Git worktree setup
- Isolation configuration
- Port allocation patterns

Coverage Scoring

ComponentPointsPresent?
.claude/​commands/20
specs/15
adws/25
adw_modules/​agent.py20
hooks/10
agents/5
trees/5

Total: 100 points

ScoreLevelRecommendation
0-20NoneStart with minimum viable layer
21-40BasicAdd composed workflows
41-60DevelopingAdd hooks and triggers
61-80AdvancedAdd worktree isolation
81-100CompleteFocus on optimization

Key Memory References

  • @agentic-layer-structure.md - What to look for
  • @the-guiding-question.md - Why this matters
  • @agentic-vs-application.md - Layer separation

Output Format

## Agentic Layer Audit Report

**Project:** {name}
**Audit Date:** {date}
**Coverage Score:** {score}/​100

### Components Found
- [x] .claude/​commands/ (5 templates)
- [x] specs/ (12 specs)
- [ ] adws/ (not found)
- [ ] hooks/ (not found)

### Maturity Level
{Level} - {Recommendation}

### Gaps Identified
1. No ADW scripts for workflow orchestration
2. No hooks for event-driven automation
3. No worktree isolation for parallelization

### Recommended Investments
1. Create adws/​adw_modules/​agent.py
2. Add gateway script (adw_prompt.py)
3. Create composed workflow for common tasks

### Time Investment Analysis
- Current: ~20% agentic layer
- Target: 50%+ agentic layer
- Gap: Need 30% more investment in agentic work

Anti-Patterns to Identify

  • Commands exist but no specs (templates unused)
  • Specs exist but no ADWs (manual execution)
  • Many one-off scripts instead of composed workflows
  • Application layer dominant (>70% of codebase)

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101