Agent skill

test-orchestrator

Test ClaudeKit workflows by scanning commands/agents/skills, generating test scenarios, and executing step-by-step with manual verification.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/test-orchestrator

SKILL.md

Test Orchestrator

Automated testing framework for ClaudeKit Marketing workflows.

When to Use

  • Testing new commands after implementation
  • Validating agent orchestration flows
  • Verifying skill integrations work correctly
  • Regression testing after changes
  • End-to-end workflow validation

Workflow

1. Scan Components

bash
# Generate fresh catalogs
python .claude/scripts/generate_catalogs.py --all

# Or scan specific type
python .claude/skills/test-orchestrator/scripts/scan-components.py

2. Select Test Scope

Scope Description
command Test single command with happy case
workflow Test multi-step workflow
integration Test skill + agent + command together
full Complete end-to-end test suite

3. Execute Tests

Each test step pauses for manual verification:

[STEP 1/5] Executing: /youtube:social "https://youtube.com/..."
─────────────────────────────────────────────────
[OUTPUT]
...generated content...
─────────────────────────────────────────────────
[VERIFY] Check output matches expected format
[PASS/FAIL?] > _

Test Case Format

yaml
name: youtube-to-social-flow
description: Convert YouTube video to multi-platform social posts
type: integration

steps:
  - name: Extract video data
    action: vidcap summary
    input: "https://youtube.com/watch?v=dQw4w9WgXcQ"
    verify:
      - Response contains video title
      - Response contains summary content

  - name: Generate social posts
    action: /youtube:social
    input: "{video_url}"
    verify:
      - Twitter post under 280 chars
      - LinkedIn post has professional tone
      - No anti-pattern hooks used

  - name: Apply writing style
    action: copywriting skill
    input: Apply casual style to Twitter post
    verify:
      - Contains contractions
      - Uses first-person

Pre-Built Test Scenarios

1. YouTube Pipeline

Step Command/Skill Input Verify
1 vidcap.py info YouTube URL Returns title, views, duration
2 vidcap.py summary YouTube URL Returns structured summary
3 /youtube:social YouTube URL Multi-platform posts generated
4 /youtube:blog YouTube URL SEO article generated
5 /youtube:infographic YouTube URL Visual layout generated

2. Content Creation

Step Command/Skill Input Verify
1 /content:blog Topic Article with frontmatter
2 /content:cro Article CRO-optimized version
3 /social Article summary Platform posts

3. Email Automation

Step Command/Skill Input Verify
1 /email:flow welcome 5-email sequence
2 email-marketing skill Sequence Timing + decision branches
3 copywriting skill Email body PAS/AIDA formula applied

4. Brand Consistency

Step Command/Skill Input Verify
1 inject-brand-context.cjs - Returns brand JSON
2 /brand:update preset Tokens synced
3 Content generation Any Brand voice applied

Happy Case Prompts

Pre-validated inputs that should always succeed:

yaml
youtube_url: "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
blog_topic: "10 productivity tips for remote workers"
email_flow: "welcome"
brand_preset: "ocean-professional"
social_platform: "twitter"
writing_style: "casual"

Manual Verification Checklist

At each step, verify:

  • Output format matches expected structure
  • No error messages in response
  • Content quality acceptable
  • Anti-patterns avoided (for hooks)
  • Brand voice consistent (if applicable)
  • File saved to correct path (if applicable)

Integration

Use with:

  • /test command to launch test runner
  • debugging skill for failure analysis
  • code-review skill for output validation

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