signalpilot

Provide governed read-only database access workflows for dbt and SQL.

475|25|Updated Mar 31, 2026
One-click install
npx skills add https://github.com/SignalPilot-Labs/SignalPilot --skill signalpilot
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: signalpilot
Source: https://github.com/SignalPilot-Labs/SignalPilot/tree/main/benchmark/signalpilot-plugin/skills/signalpilot
Command: npx skills add https://github.com/SignalPilot-Labs/SignalPilot --skill signalpilot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SignalPilot's governed AI database access provides a safe, auditable layer for interacting with data warehouses. It exposes MCP tools for read-only SQL, schema discovery, and dbt validation to reduce risk and enforce enterprise policies.

Core Features & Use Cases

  • Governed MCP tools: query_database, validate_sql, explain_query, schema_overview, and more for controlled data access.
  • Schema discovery & validation: explore_table, describe_table, audit_model_sources, and related tools to understand data structures.
  • dbt workflow support: validated dbt project interactions and project management tools to ensure reliable analytics pipelines.
  • Local scripts for dbt projects: optional utilities such as scan_project.py and validate_project.py to streamline project audits.

Quick Start

Load /signalpilot-dbt:dbt-workflow to orchestrate scanning, mapping, validating, writing, and verifying a dbt project.

Frequently Asked Questions about signalpilot

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

FAQPage Schema
How do I provide governed read-only SQL access for dbt workflows?▼

Governed read-only SQL access for dbt workflows is provided through MCP tools that enforce strict safety guards, enabling query validation and schema discovery without write risks.

Can I use this governed database access with Snowflake, BigQuery, and Postgres?▼

Yes, governed database access supports Snowflake, BigQuery, and Postgres, allowing data engineers to execute read-only queries and explore schemas across these data warehouse platforms.

What is the best way to perform schema discovery before validating a dbt project?▼

Schema discovery before dbt project validation is handled using tools like schema_overview, explore_table, and describe_table to understand data structures and audit model sources safely.

How do I validate SQL queries to enforce enterprise data access policies?▼

SQL query validation to enforce enterprise data access policies is achieved using the validate_sql MCP tool, ensuring query execution remains read-only, safe, and auditable.

Are there local scripts available to scan and validate dbt projects?▼

Yes, local utilities like scan_project.py and validate_project.py are available to streamline dbt project scanning, mapping, and validation within a governed workflow.

Why should data engineers use MCP tools for database access instead of direct connections?▼

Data engineers use MCP tools for database access to reduce risk and enforce enterprise policies, providing a safe, auditable layer that direct connections lack for analytics pipelines.