How do I install the Squit Data skill?

Run npx skillmds@latest add deagentic/squit-data in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Squit Data safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Squit Data?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Squit Data free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Squit Data?

deagentic (@deagentic) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Squit Data by deagentic — Agent Skill

Name: Squit Data
Author: deagentic

File contents

SQUIT Data Discovery

Identity

This skill specializes the SQUIT semantic search capability for pipeline data discovery use cases. While the base squit skill (in the archaeology capability) is oriented toward code exploration and impact analysis, squit-data focuses on discovering data shapes, table schemas, and object-to-dataset mappings needed for Kedro catalog registration.

Scope

Schema discovery: Finding the column structure, data types, and constraints of tables and views.
Dataset mapping: Mapping legacy SQL objects (tables, views, result sets of procedures) to typed Kedro datasets.
Source identification: Finding which SQL servers and databases contain data relevant to a pipeline.
Lineage tracing: Using squit_dependencies to trace how data moves through the legacy SQL layer.
Volume estimation: Understanding approximate data volumes for partitioning and resource planning decisions.

Workflow

1. Invoke squit_search with data-focused queries:
   - "tabla clientes columnas" → finds ClientesMaster schema
   - "view ventas diarias estructura" → finds vw_VentasDiarias definition

2. Invoke squit_get_code to retrieve full DDL/CREATE statements for schema extraction.

3. Invoke squit_dependencies to identify upstream data producers (INSERT/UPDATE sources).

4. Map discovered schemas to Kedro dataset types in catalog.yml.

Status

This skill is a stub. Full implementation will integrate SQUIT's vector search with a schema extraction pipeline that automatically generates Kedro catalog entries from discovered SQL objects. Implementation is gated on ADR-0030.

Related Skills

squit (from archaeology) — base SQUIT MCP server access
deacero-domain — business context for discovered schemas
kedro-builder — consumes the catalog entries produced by this skill

---name: squit-datadescription: Use when querying DeAcero's data catalog, discovering table schemas, or mapping legacy SQL objects to Kedro datasets. Invoke before building any Kedro pipeline node that touches DeAcero data sources.---# SQUIT Data Discovery## IdentityThis skill specializes the SQUIT semantic search capability for pipeline data discovery use cases. While the base `squit` skill (in the `archaeology` capability) is oriented toward code exploration and impact analysis, `squit-data` focuses on discovering data shapes, table schemas, and object-to-dataset mappings needed for Kedro catalog registration.## Scope- **Schema discovery**: Finding the column structure, data types, and constraints of tables and views.- **Dataset mapping**: Mapping legacy SQL objects (tables, views, result sets of procedures) to typed Kedro datasets.- **Source identification**: Finding which SQL servers and databases contain data relevant to a pipeline.- **Lineage tracing**: Using `squit_dependencies` to trace how data moves through the legacy SQL layer.- **Volume estimation**: Understanding approximate data volumes for partitioning and resource planning decisions.## Workflow```1. Invoke squit_search with data-focused queries: - "tabla clientes columnas" → finds ClientesMaster schema - "view ventas diarias estructura" → finds vw_VentasDiarias definition2. Invoke squit_get_code to retrieve full DDL/CREATE statements for schema extraction.3. Invoke squit_dependencies to identify upstream data producers (INSERT/UPDATE sources).4. Map discovered schemas to Kedro dataset types in catalog.yml.```## StatusThis skill is a stub. Full implementation will integrate SQUIT's vector search with a schema extraction pipeline that automatically generates Kedro catalog entries from discovered SQL objects. Implementation is gated on ADR-0030.## Related Skills- `squit` (from `archaeology`) — base SQUIT MCP server access- `deacero-domain` — business context for discovered schemas- `kedro-builder` — consumes the catalog entries produced by this skill

Frequently asked questions

Squit Data