skill-integration-tester
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.
By tradermonty · 1,939 installs
npx skills add tradermonty/claude-trading-skills --skill skill-integration-tester
Source repository · Upstream listing
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:
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:
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:
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
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