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treasure-data
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validate-journey

Validate Journey YAML definitions against Treasure Data schema constraints.

21|24|Updated Oct 21, 2025
Search Tags:#validation#yaml#journey#tdx
One-click install
npx skills add https://github.com/treasure-data/td-skills --skill validate-journey
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validate-journey
Source: https://github.com/treasure-data/td-skills/tree/main/tdx-skills/validate-journey
Command: npx skills add https://github.com/treasure-data/td-skills --skill validate-journey

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Validates CDP journey YAML against the TD schema, helping catch structural and semantic errors before pushing to Treasure Data.

Core Features & Use Cases

  • Validation of type, structure, and step parameters
  • Quick checks for segment references and activations

Quick Start

Run tdx sg validate or validate a specific journey YAML file: tdx sg validate path/to/journey.yml.

Frequently Asked Questions about validate-journey

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

FAQPage Schema
How do I validate journey YAML before pushing to Treasure Data?▼

Journey YAML validation checks your configuration against TD schema using `tdx sg validate` or `tdx sg validate path/to/journey.yml`. This catches structural errors, type mismatches, and parameter issues before deployment, preventing runtime failures in your CDP workflows.

What journey configuration limits does validation enforce?▼

Validation enforces TD journey limits: 8 stages maximum, 120 events per journey, 70 events per stage, and 30 versions. It also verifies per-type field requirements for wait, activation, decision_point, ab_test, merge, jump, and end steps.

Can validation check segment references in journey definitions?▼

Yes, validation verifies segment references and activation parameters, catching misconfigurations in both embedded and external segment usage. It ensures segments referenced in your journey steps exist and are correctly parameterized.

What errors does journey validation detect?▼

Validation detects type errors, missing required fields per step type, invalid next step placement, misconfigured segment references, and violations of journey structural limits. It identifies configuration mistakes early without requiring deployment.

When should I run journey validation in my workflow?▼

Run validation whenever you create or modify a journey YAML file, especially before pushing changes to Treasure Data. Use it during development and review to catch configuration errors early and avoid deployment issues.

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