Workflow Validate

Validate Betty workflow YAML definitions for schema correctness and structural integrity.

2|Updated Oct 22, 2025
One-click install
npx skills add https://github.com/epieczko/betty --skill workflow-validate
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Workflow Validate
Source: https://github.com/epieczko/betty/tree/main/skills/workflow.validate
Command: npx skills add https://github.com/epieczko/betty --skill workflow-validate

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyYAML, pydantic.

What problem does it solve?

Ensures workflow YAML definitions include required fields and conform to schema before runtime execution.

Core Features & Use Cases

  • Validates required fields (e.g., steps)
  • Checks step structure for skill/agent usage
  • Optional: resolves skill versions against registry
  • Produces structured validation results

Quick Start

python skills/workflow.validate/workflow_validate.py workflows/example.yaml

Frequently Asked Questions about Workflow Validate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate workflow YAML files before running them?

Workflow validation checks YAML structure for required fields like 'steps' and ensures each step contains either a 'skill' (with 'version' and 'args') or 'agent' (with optional 'input'). Run the validator against your YAML file to get a detailed JSON report with status, errors, and path information before execution.

What schema requirements must my Betty workflow YAML meet?

Your workflow must include a top-level 'steps' field where each step is a mapping. Steps must define either a skill with required 'version' and 'args' fields, or an agent with optional 'input'. The validator checks field types and resolves skill versions against the local registry.

Can I catch YAML and schema errors before runtime?

Yes. The validator produces structured validation results that catch invalid YAML syntax, missing required fields, type mismatches, and unresolved skill versions, returning detailed error messages so you can fix issues before execution.

Does the validator resolve skill versions automatically?

The validator optionally resolves skill versions against your local registry as part of validation. This ensures the skills referenced in your workflow steps actually exist and are available at the specified versions.

What dependencies do I need to run workflow validation?

Workflow validation requires PyYAML for parsing YAML files and Pydantic for schema validation and type checking. Both are listed as dependencies and handle the structural integrity checks.

What output format does the validator produce?

The validator produces a JSON report containing 'ok' status, validation status, detailed error list, and workflow path. This structured output makes it easy to parse results programmatically or display validation feedback.