clickhouse-pydantic-config_skill

This skill generates DBeaver connection configurations from Pydantic ClickHouse models, enabling seamless environment-based data sources and cloud/local

TypeScript

14

GitHub Stars

1

Bundled Files

3 weeks ago

Catalog Refreshed

2 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstart where the catalogue uses aiagentskills.

npx veilstart add skill terrylica/cc-skills --skill clickhouse-pydantic-config

SKILL.md8.1 KB

Overview

This skill generates DBeaver data-source configurations from Pydantic v2 ClickHouse models, using mise [env] values as the Single Source of Truth. It produces ready-to-import .dbeaver data-sources JSON entries for local and cloud ClickHouse profiles while respecting environment-driven credentials and repo conventions. The output is intended to be adapted to each repository’s layout and naming rules.

How this skill works

The skill loads ClickHouse connection settings from the mise [env] section or .env fallbacks and validates them with a Pydantic ClickHouseConnection model. It constructs mode-aware configuration fields (JDBC URL, driver, SSL/port) and emits DBeaver-compatible JSON entries, optionally pre-populating credentials for cloud mode. It can run in dry-run preview, local generation, or cloud generation flows and integrates with credential retrieval steps when needed.

When to use it

When setting up DBeaver connections for ClickHouse databases
When you want database client configs generated from environment variables
When managing local versus cloud ClickHouse connection profiles
When integrating ClickHouse config generation into mise-based workflows
When automating creation or updates of DBeaver data-sources.json

Best practices

Treat mise [env] as the repository Single Source of Truth and map any non-standard env names to that SSoT
Preserve and merge with existing .dbeaver entries instead of overwriting to avoid losing other connections
Use dry-run to preview generated JSON and validate with a JSON linter before writing
Keep generated data-sources.json gitignored; pre-populate cloud credentials from a gitignored .env for convenience
Verify connectivity and DBeaver import after generation and restart DBeaver if caching prevents updates

Example use cases

Generate a local DBeaver profile for a developer machine using default user and HTTP port
Create a cloud-readonly DBeaver connection by pulling credentials from .env after retrieving them via a credential management skill
Automate CI or developer onboarding by adding a mise task that emits data-sources.json during setup
Produce multiple connection entries when a repo uses both local and cloud ClickHouse instances
Run dry-run in CI to validate configuration structure without committing secrets

FAQ

No — the recommended workflow is to detect and merge with existing .dbeaver entries. If merging is not possible, the tool warns and can write a separate file to avoid data loss.

How are credentials handled for cloud mode?

Cloud mode reads credentials from environment (.env) and pre-populates the generated data-sources.json. The JSON should remain gitignored; credentials are not committed.