api-warehouse
NewPoint a coding agent at any API's docs → client-ready assessment, sample data, and raw data landed in your warehouse (BigQuery/Snowflake/Postgres/Azure/files). A Claude Code plugin. Raw-landing only, security-first, validated.
Summary
This skill enables a coding agent to ingest any API's documentation, produce a client-ready assessment, generate sample data, and land raw data directly into your warehouse (BigQuery, Snowflake, Postgres, Azure, or files).
- It follows a security-first, validated approach to raw-landing only, making it ideal for developers who need to quickly integrate external APIs without compromising security.
Install & Usage
mkdir -p .claude/skillsAdd the configuration to .claude/skills/api-warehouse.md
/api-warehouseUse Cases
Usage Examples
/api-warehouse assess https://api.example.com/docs -o security-report.md
Generate sample data from the Stripe API docs and land it into my Postgres raw schema.
/api-warehouse land https://api.github.com/v3 -w bigquery://my-project:raw_dataset --validate
Security Audits
Frequently Asked Questions
What is api-warehouse?
This skill enables a coding agent to ingest any API's documentation, produce a client-ready assessment, generate sample data, and land raw data directly into your warehouse (BigQuery, Snowflake, Postgres, Azure, or files). It follows a security-first, validated approach to raw-landing only, making it ideal for developers who need to quickly integrate external APIs without compromising security.
How to install api-warehouse?
To install api-warehouse: create the skills directory (mkdir -p .claude/skills), then add the config to .claude/skills/api-warehouse.md. Finally, /api-warehouse in Claude Code.
What is api-warehouse best for?
api-warehouse is a other categorized under General. It is designed for: security, api, agent, plugin. Created by sdhilip200.
What can I use api-warehouse for?
api-warehouse is useful for: Assess a new third-party API by pointing the agent at its docs to get a security and compatibility report before integration.; Generate realistic sample data from an API's schema to test your data pipeline without hitting the live endpoint.; Land raw API responses directly into BigQuery for downstream analytics, with automatic schema inference and validation.; Validate API responses against documented schemas to catch breaking changes or unexpected data formats.; Create a raw landing zone in Snowflake for an API's data, ensuring all fields are preserved for future transformation.; Export raw API data to local files (JSON/CSV) for offline analysis or archival, with security checks on sensitive fields..