name: agent:review description: Agent Pattern Review - validates an AI agent against all 22 patterns from "Patterns for Building AI Agents" with a scored checklist and recommendations argument-hint: [spec-name|path]
Agent Pattern Review
Reviews an existing AI agent (or agent design) against all 22 patterns from "Patterns for Building AI Agents" (Bhagwat & Gienow, 2025). Produces a scored checklist with specific recommendations for improvement.
When to use
Use this skill when the user needs to:
- Validate an existing agent against industry best practices
- Get a comprehensive health check of an agent system
- Identify the highest-impact improvements
- Prepare for production readiness
Instructions
Step 1: Gather Agent Information
Use the AskUserQuestion tool to understand what to review:
- Is there a spec? (check
.specs/<spec-name>/) - Is there agent code to analyze? (path to source)
- Is this a design review (documents only) or implementation review (code + documents)?
Read all available materials:
- Spec documents:
agent-design.md,context-engineering.md,agent-eval.md,agent-security.md - Source code: agent definitions, tool implementations, prompt templates
- Configuration: model settings, guardrail configs, access policies
Step 2: Score All 22 Patterns
For each pattern, assess the current state. Use this scoring:
- N/A — Not applicable to this agent
- 0 - Not Started — Pattern not addressed
- 1 - Basic — Partially addressed, significant gaps
- 2 - Good — Mostly addressed, minor gaps
- 3 - Excellent — Fully addressed, follows best practices
Evaluate using parallel sub-agents (subagent_type: "Explore") where code analysis is needed.
Step 3: Generate Review Report
# Agent Pattern Review: [System Name]
**Date:** [Date]
**Scope:** [Design / Implementation / Both]
**Overall Score:** [X / 66] ([Y%])
---
## Part I: Configure Your Agents ([X/12])
| # | Pattern | Score | Evidence | Recommendation |
|---|---------|-------|----------|----------------|
| 1 | Whiteboard Agent Capabilities | [0-3] | [What exists] | [What to improve] |
| 2 | Evolve Your Agent Architecture | [0-3] | [What exists] | [What to improve] |
| 3 | Dynamic Agents | [0-3] | [What exists] | [What to improve] |
| 4 | Human-in-the-Loop | [0-3] | [What exists] | [What to improve] |
## Part II: Engineer Agent Context ([X/15])
| # | Pattern | Score | Evidence | Recommendation |
|---|---------|-------|----------|----------------|
| 5 | Parallelize Carefully | [0-3] | [What exists] | [What to improve] |
| 6 | Share Context Between Subagents | [0-3] | [What exists] | [What to improve] |
| 7 | Avoid Context Failure Modes | [0-3] | [What exists] | [What to improve] |
| 8 | Compress Context | [0-3] | [What exists] | [What to improve] |
| 9 | Feed Errors Into Context | [0-3] | [What exists] | [What to improve] |
## Part III: Evaluate Agent Responses ([X/24])
| # | Pattern | Score | Evidence | Recommendation |
|---|---------|-------|----------|----------------|
| 10 | List Failure Modes | [0-3] | [What exists] | [What to improve] |
| 11 | List Critical Business Metrics | [0-3] | [What exists] | [What to improve] |
| 12 | Cross-Reference Failure Modes and Metrics | [0-3] | [What exists] | [What to improve] |
| 13 | Iterate Against Your Evals | [0-3] | [What exists] | [What to improve] |
| 14 | Create an Eval Test Suite | [0-3] | [What exists] | [What to improve] |
| 15 | Have SMEs Label Data | [0-3] | [What exists] | [What to improve] |
| 16 | Create Datasets from Production Data | [0-3] | [What exists] | [What to improve] |
| 17 | Evaluate Production Data | [0-3] | [What exists] | [What to improve] |
## Part IV: Secure Your Agents ([X/12])
| # | Pattern | Score | Evidence | Recommendation |
|---|---------|-------|----------|----------------|
| 18 | Prevent the Lethal Trifecta | [0-3] | [What exists] | [What to improve] |
| 19 | Sandbox Code Execution | [0-3] | [What exists] | [What to improve] |
| 20 | Granular Agent Access Control | [0-3] | [What exists] | [What to improve] |
| 21 | Agent Guardrails | [0-3] | [What exists] | [What to improve] |
## Part V: Future-Readiness ([X/3])
| # | Pattern | Score | Evidence | Recommendation |
|---|---------|-------|----------|----------------|
| 22 | What's Next (Simulations, Learning, Synthetic Evals) | [0-3] | [What exists] | [What to improve] |
---
## Score Summary
| Part | Score | Max | Percentage |
|------|-------|-----|-----------|
| I. Configure | [X] | 12 | [Y%] |
| II. Context | [X] | 15 | [Y%] |
| III. Evaluate | [X] | 24 | [Y%] |
| IV. Secure | [X] | 12 | [Y%] |
| V. Future | [X] | 3 | [Y%] |
| **Total** | **[X]** | **66** | **[Y%]** |
---
## Top 5 Recommendations
Ranked by impact and effort:
| # | Recommendation | Pattern | Impact | Effort | Priority |
|---|---------------|---------|--------|--------|----------|
| 1 | [Recommendation] | [Pattern #] | High | Low | P0 |
| 2 | [Recommendation] | [Pattern #] | High | Medium | P0 |
| 3 | [Recommendation] | [Pattern #] | Medium | Low | P1 |
| 4 | [Recommendation] | [Pattern #] | Medium | Medium | P1 |
| 5 | [Recommendation] | [Pattern #] | Medium | High | P2 |
---
## Maturity Assessment
| Level | Score Range | Description |
|-------|-----------|-------------|
| **Prototype** | 0-20% | Agent works but lacks production safeguards |
| **MVP** | 21-45% | Core patterns in place, gaps in eval and security |
| **Production-Ready** | 46-70% | Solid foundation, iterating on quality |
| **Mature** | 71-90% | Comprehensive coverage, continuous improvement |
| **Best-in-Class** | 91-100% | Industry-leading agent practices |
**Current maturity: [Level]**
Step 4: Offer Next Steps
Use AskUserQuestion to offer targeted actions based on the weakest areas:
- Run
agent:design— if Part I scored low - Run
agent:context— if Part II scored low - Run
agent:eval— if Part III scored low - Run
agent:secure— if Part IV scored low
Arguments
$ARGUMENTS($0) - Optional spec name or path to agent code<spec-name>— reviews agent from.specs/<spec-name>/<path>— reviews agent code at the given path
Examples:
agent:review customer-support— review the customer-support agentagent:review src/agents/— review agent code in the given directoryagent:review— will ask what to review