microsoft/waza · Archived

waza-runner

Run evaluations on Agent Skills to measure their effectiveness. USE FOR: "run skill evals", "evaluate my skill", "test skill quality", "check skill triggers", "skill compliance check", "measure skill performance", "run evals on [skill-name]", "grade skill execution". DO NOT USE FOR: writing skills (use skill-authoring), improving frontmatter (use sensei), or general testing unrelated to skills.

First seen May 13, 2026

Installation

$ npx skills add microsoft/waza --skill waza-runner

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 1.3K
License LICENSE
Default branch main
Open issues 10
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0
More metadata
author
spboyer
version
1.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,457 B
  • docs SUMMARY.md 416 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 13 installs

SKILL.md

Skill Eval Runner

Evaluate Agent Skills like you evaluate AI Agents

This skill runs evaluations on other skills to measure their effectiveness using the same patterns that power AI agent evaluations.

When to Use

  • Running quality evaluations on a skill
  • Testing if a skill triggers on correct prompts
  • Measuring skill behavior quality
  • Generating eval reports for CI/CD

Commands

Run Evals

Run evals on <skill-name>

Initialize Eval Suite

Create evals for <skill-name>

Generate Report

Generate eval report for <skill-name>

Workflow

  1. Check for Eval Suite: Look for eval.yaml in the skill directory
  2. Load Tasks: Parse task definitions from tasks/*.yaml
  3. Execute: Run each task through the configured graders
  4. Report: Output results in JSON or Markdown format

Metrics Measured

Metric Description Default Threshold
Task Completion Did the skill accomplish the goal? 80%
Trigger Accuracy Was skill invoked on correct prompts? 90%
Behavior Quality Tool calls, efficiency, reasoning 70%

Grader Types

  • Code Graders: Deterministic assertions, regex matching
  • LLM Graders: Model-as-judge with configurable rubrics
  • Human Graders: Manual review workflow

Example Usage

Running Evals

# From CLI
waza run ./my-skill/eval.yaml

# Output to file
waza run ./my-skill/eval.yaml -o results.json

Interpreting Results

{
  "summary": {
    "pass_rate": 0.85,
    "composite_score": 0.82
  },
  "metrics": {
    "task_completion": { "score": 0.9, "passed": true },
    "trigger_accuracy": { "score": 0.95, "passed": true }
  }
}

References

  • [Eval Specification](references/EVAL-SPEC.md) - Full eval.yaml schema
  • [Writing Tasks](references/WRITING-TASKS.md) - Task definition guide
  • [Grader Reference](references/GRADERS.md) - Available graders