Skill Integration Tester Skill for Claude

Skill Integration Tester

Overview

Validate multi-skill workflows defined in CLAUDE.md (Daily Market Monitoring,

Weekly Strategy Review, Earnings Momentum Trading, etc.) by executing each step

in sequence. Check inter-skill data contracts for JSON schema compatibility

between output of step N and input of step N+1, verify file naming conventions,

and report broken handoffs. Supports dry-run mode with synthetic fixtures.

When to Use

• After adding or modifying a multi-skill workflow in CLAUDE.md
• After changing a skill's output format (JSON schema, file naming)
• Before releasing new skills to verify pipeline compatibility
• When debugging broken handoffs between consecutive workflow steps
• As a CI pre-check for pull requests touching skill scripts

Prerequisites

• Python 3.9+
• No API keys required
• No third-party Python packages required (uses only standard library)

Workflow

Step 1: Run Integration Validation

Execute the validation script against the project's CLAUDE.md:

python3 skills/skill-integration-tester/scripts/validate_workflows.py \
  --output-dir reports/

This parses all Workflow Name: blocks from the Multi-Skill Workflows

section, resolves each step's display name to a skill directory, and validates

existence, contracts, and naming.

Step 2: Validate a Specific Workflow

Target a single workflow by name substring:

python3 skills/skill-integration-tester/scripts/validate_workflows.py \
  --workflow "Earnings Momentum" \
  --output-dir reports/

Step 3: Dry-Run with Synthetic Fixtures

Create synthetic fixture JSON files for each skill's expected output and

validate contract compatibility without real data:

python3 skills/skill-integration-tester/scripts/validate_workflows.py \
  --dry-run \
  --output-dir reports/

Fixture files are written to reports/fixtures/ with _fixture flag set.

Step 4: Review Results

Open the generated Markdown report for a human-readable summary, or parse

the JSON report for programmatic consumption. Each workflow shows:

• Step-by-step skill existence checks
• Handoff contract validation (PASS / FAIL / N/A)
• File naming convention violations
• Overall workflow status (valid / broken / warning)

Step 5: Fix Broken Handoffs

For each FAIL handoff, verify that:

• The producer skill's output contains all required fields
• The consumer skill's input parameter accepts the producer's output format
• File naming patterns are consistent between producer output and consumer input

Output Format

JSON Report

{
  "schema_version": "1.0",
  "generated_at": "2026-03-01T12:00:00+00:00",
  "dry_run": false,
  "summary": {
    "total_workflows": 8,
    "valid": 6,
    "broken": 1,
    "warnings": 1
  },
  "workflows": [
    {
      "workflow": "Daily Market Monitoring",
      "step_count": 4,
      "status": "valid",
      "steps": [...],
      "handoffs": [...],
      "naming_violations": []
    }
  ]
}

Markdown Report

Structured report with per-workflow sections showing step validation,

handoff status, and naming violations.

Reports are saved to reports/ with filenames

integration_test_YYYY-MM-DD_HHMMSS.{json,md}.

Resources

• scripts/validate_workflows.py -- Main validation script
• references/workflow_contracts.md -- Contract definitions and handoff patterns

Key Principles

• No API keys required -- all validation is local and offline
• Non-destructive -- reads SKILL.md and CLAUDE.md only, never modifies skills
• Deterministic -- same inputs always produce same validation results