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/skill-integration-tester

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Validate multi-skill workflows defined in CLAUDE.md by checking skill existence, inter-skill data contracts (JSON schema compatibility), file naming conventions, and handoff integrity. Use when adding new workflows, modifying skill outputs, or verifying pipeline health before release.

Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/skill-integration-tester

This session only. Nothing lands on disk.

SKILL.md

≈78 tokens always: the name and description. ≈904 when used: this file. ≈878 more on demand in 1 file.

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:

  1. The producer skill's output contains all required fields
  2. The consumer skill's input parameter accepts the producer's output format
  3. 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

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

Source: SKILL.md on GitHub

No alerts17d5 checks · Risk SAFE
  • Gen Agent Trust Hub17d

    The skill is a local utility for validating skill workflows and JSON data contracts within a project. It operates entirely offline using the Python standard library, with no network access, privilege escalation, or dynamic code execution. No security issues were detected.

  • Socket17d

    No alerts

  • Snyk17d

    Risk: LOW · No issues

  • Runlayer6mo

    1/5 files flagged

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at c3b5cda. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 19 hours ago.

Activeupdated 6 months ago
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