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sharpdeveye/maestro346 installs

evaluate

Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.

How do I install this agent skill?

npx skills add https://github.com/sharpdeveye/maestro --skill evaluate
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill is safe. It provides structured guidance and a methodology for auditing and evaluating the interaction quality of workflows against realistic scenarios without introducing any technical risk or malicious patterns.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

MANDATORY PREPARATION

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.

Evaluation Dimensions

1. Task Completion

  • Does the workflow actually accomplish what it's supposed to?
  • Does it handle the complete task or only the happy path?
  • Are edge cases addressed or silently dropped?

2. Output Quality

  • Is the output accurate, complete, and well-formatted?
  • Does it match the defined output schema (if any)?
  • Would a domain expert approve the output?

3. Error Behavior

  • What happens when input is malformed?
  • What happens when a tool fails?
  • What happens when the model is uncertain?
  • Is the error message useful or generic?

4. User Experience

  • Is the interaction natural and intuitive?
  • Are confirmations requested for destructive operations?
  • Is the response time acceptable?
  • Does the workflow communicate its limitations?

5. Consistency

  • Does the same input produce consistent output quality?
  • Are there random failures that aren't reproducible?
  • Does quality degrade over long conversations?

Scenario Testing

Create and run test scenarios:

ScenarioInputExpectedActualGrade
Happy pathNormal inputCorrect output?A-F
Edge caseUnusual inputGraceful handling?A-F
Error caseBad inputHelpful error?A-F
Stress caseLarge/complex inputReasonable handling?A-F
AdversarialTricky/malicious inputSafe response?A-F

Evaluation Report

Produce a structured report with:

  1. Overall quality grade (A-F)
  2. Per-dimension scores with evidence
  3. Specific scenario results
  4. Priority improvements with recommended Maestro commands

Evaluation Checklist

  • All 5 dimensions tested with concrete scenarios
  • At least one edge case and one adversarial case tested
  • Results documented in the scenario table
  • Overall grade assigned with justification
  • Improvement actions reference specific Maestro commands

Recommended Next Step

After evaluation, run /fortify to address error behavior gaps, /refine for output quality improvements, or /iterate to set up continuous quality monitoring.

NEVER:

  • Evaluate theoretically — run actual scenarios
  • Give an A grade unless the workflow handles all scenario types well
  • Skip adversarial testing for user-facing workflows
  • Evaluate only the happy path

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/sharpdeveye/maestro/evaluate">View evaluate on skillZs</a>