From tac
Audits codebase for agentic layer maturity: checks .claude/commands, specs, adws, hooks, agents, trees; computes coverage score and identifies gaps.
How this skill is triggered — by the user, by Claude, or both
Slash command
/tac:agentic-layer-auditThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Evaluate a codebase's agentic layer maturity and identify investment opportunities.
Evaluate a codebase's agentic layer maturity and identify investment opportunities.
"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.
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
Check for specs/ or equivalent:
Look for:
- Issue-based specs (issue-*.md)
- Generated plans (chore-*.md, feature-*.md)
- Deep specs (complex multi-file architectures)
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)
Check for .claude/hooks/ or equivalent:
Look for:
- pre_tool_use hooks
- post_tool_use hooks
- user_prompt_submit hooks
Check for agents/ or equivalent:
Look for:
- ADW ID directories
- State files (adw_state.json)
- Output files (cc_*.jsonl, cc_*.json)
Check for trees/ or equivalent:
Look for:
- Git worktree setup
- Isolation configuration
- Port allocation patterns
| Component | Points | Present? |
|---|---|---|
| .claude/commands/ | 20 | |
| specs/ | 15 | |
| adws/ | 25 | |
| adw_modules/agent.py | 20 | |
| hooks/ | 10 | |
| agents/ | 5 | |
| trees/ | 5 |
Total: 100 points
| Score | Level | Recommendation |
|---|---|---|
| 0-20 | None | Start with minimum viable layer |
| 21-40 | Basic | Add composed workflows |
| 41-60 | Developing | Add hooks and triggers |
| 61-80 | Advanced | Add worktree isolation |
| 81-100 | Complete | Focus on optimization |
## 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
Date: 2025-12-26 Model: claude-opus-4-5-20251101
npx claudepluginhub melodic-software/claude-code-plugins --plugin tacAudits codebase for agentic layer maturity: scores .claude/commands, specs, adws/agent.py, hooks, agents/trees dirs; identifies gaps and investment opportunities.
Assesses codebase for AI agent readiness by detecting stacks, monorepos, git setup, and evaluating style, testing, code quality, secrets, and file sizes.
Audits agent codebases against the 12-Factor Agents methodology, analyzing per-factor compliance with file-level evidence. Use when reviewing LLM-powered system architecture or planning agent improvements.