agent-orchestration-improve-agent

version	4.1.0-fractal
name	agent-orchestration-improve-agent
description	Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

Agent Performance Optimization Workflow

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

[Extended thinking: Agent optimization requires a data-driven approach combining performance metrics, user feedback analysis, and advanced prompt engineering techniques. Success depends on systematic evaluation, targeted improvements, and rigorous testing with rollback capabilities for production safety.]

Use this skill when

• Improving an existing agent's performance or reliability
• Analyzing failure modes, prompt quality, or tool usage
• Running structured A/B tests or evaluation suites
• Designing iterative optimization workflows for agents

Do not use this skill when

• You are building a brand-new agent from scratch
• There are no metrics, feedback, or test cases available
• The task is unrelated to agent performance or prompt quality

Instructions

1. Establish baseline metrics and collect representative examples.
2. Identify failure modes and prioritize high-impact fixes.
3. Apply prompt and workflow improvements with measurable goals.
4. Validate with tests and roll out changes in controlled stages.

Safety

• Avoid deploying prompt changes without regression testing.
• Roll back quickly if quality or safety metrics regress.

Phase 1: Performance Analysis and Baseline Metrics

Comprehensive analysis of agent performance using context-manager for historical data collection.

🧠 Knowledge Modules (Fractal Skills)

1. 1.1 Gather Performance Data

2. 1.2 User Feedback Pattern Analysis

3. 1.3 Failure Mode Classification

4. 1.4 Baseline Performance Report

5. 2.1 Chain-of-Thought Enhancement

6. 2.2 Few-Shot Example Optimization

7. 2.3 Role Definition Refinement

8. 2.4 Constitutional AI Integration

9. 2.5 Output Format Tuning

10. 3.1 Test Suite Development

11. 3.2 A/B Testing Framework

12. 3.3 Evaluation Metrics

13. 3.4 Human Evaluation Protocol

14. 4.1 Version Management

15. 4.2 Staged Rollout

16. 4.3 Rollback Procedures

17. 4.4 Continuous Monitoring