check-data-pipeline

To check ADK data pipeline scripts for hard-coded file paths, run the validation tool against your project. It scans Python tool functions to enforce file path definition rules and surfaces violations before deployment.

The correct way to access configuration in ADK ToolContext is by using app: prefixed state keys. The data pipeline validator checks your tool functions to ensure all configuration and data access strictly follows this pattern.

This validation tool is specifically designed for Python-based data pipeline tooling within ADK projects. It applies static checks to scripts, agent functions, and configuration loading to enforce ADK safety rules.

ADK tool scripts must follow function signature rules that mandate tool-context based parameter access. The validator checks your Python functions to ensure correct signatures and usage patterns, reducing data access risks.

Your ADK data pipeline check may fail on configuration loading if your scripts use hard-coded paths or lack app: prefixed state keys. The validator enforces ToolContext usage to prevent these unsafe data access patterns.

To validate ADK tool patterns before deploying a data pipeline, run the static analysis check against your project. It audits file paths, ToolContext usage, and function signatures to ensure conformity with CLAUDE.md rules.