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Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.
Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
Capture a session summary — what was done, what decisions were made, and what to do next.
| name | evaluate |
| description | Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios. |
| argument-hint | [workflow or scenario] |
| category | analysis |
| version | 2.0.0 |
| user-invocable | true |
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Consult the feedback-loops reference in the agent-workflow skill for evaluation patterns, golden test sets, and regression detection.
Evaluate the workflow's actual interaction quality by testing it against scenarios that represent real usage.
1. Task Completion
2. Output Quality
3. Error Behavior
4. User Experience
5. Consistency
Create and run test scenarios:
| Scenario | Input | Expected | Actual | Grade |
|---|---|---|---|---|
| Happy path | Normal input | Correct output | ? | A-F |
| Edge case | Unusual input | Graceful handling | ? | A-F |
| Error case | Bad input | Helpful error | ? | A-F |
| Stress case | Large/complex input | Reasonable handling | ? | A-F |
| Adversarial | Tricky/malicious input | Safe response | ? | A-F |
Produce a structured report with:
After evaluation, run /fortify to address error behavior gaps, /refine for output quality improvements, or /iterate to set up continuous quality monitoring.
NEVER:
