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

<args>
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 agent
agent:review src/agents/ — review agent code in the given directory
agent:review — will ask what to review

agent:review

Safety Notice

Copy this and send it to your AI assistant to learn

Agent Pattern Review: [System Name]

Part I: Configure Your Agents ([X/12])

Part II: Engineer Agent Context ([X/15])

Part III: Evaluate Agent Responses ([X/24])

Part IV: Secure Your Agents ([X/12])

Part V: Future-Readiness ([X/3])

Score Summary

Top 5 Recommendations

Maturity Assessment

Source Transparency

Related Skills

agent:prompt

agent:memory

agent:secure

agent:design