signalpilot

name	signalpilot
description	BLOCKING REQUIREMENT: If the user's message mentions dbt, SQL, database, or data pipeline — invoke this skill as your FIRST tool call, BEFORE Read, Glob, Grep, Bash, or Agent. Covers: SignalPilot MCP tools, available skills, and the governed workflow for dbt projects, SQL queries, schema discovery, and database access.

SignalPilot — Governed AI Database Access

User-visible Progress Contract

SignalPilot work is often tool-heavy. Keep the user oriented while you use MCP tools:

• Before the first MCP call, write one short sentence explaining what you are checking and why.
• Before each major phase, write one short progress sentence for schema scouting, query validation, model/notebook edits, execution, error repair, and final verification.
• After a tool result changes the plan, finds a data-quality issue, or fails, summarize what changed and what you will do next.
• Do not expose private reasoning, chain-of-thought, raw JSON, or every tool parameter. Explain intent and findings in human terms.
• Do not leave the user watching only MCP calls. A good run has concise assistant text between groups of tool calls.
• Final answers should mention the evidence actually checked and any residual uncertainty.

MCP Tools

The SignalPilot MCP provides governed database access:

• query_database — governed read-only SQL execution
• validate_sql / explain_query / estimate_query_cost — pre-execution checks
• schema_overview / schema_ddl / schema_link — schema discovery
• describe_table / explore_table / explore_columns / explore_column — deep dives
• list_tables / get_relationships / find_join_path — structure and joins
• compare_join_types — JOIN impact analysis
• get_date_boundaries — date ranges across all tables
• check_model_schema / validate_model_output / audit_model_sources — dbt validation
• analyze_grain — cardinality and grain analysis
• debug_cte_query — step-through CTE debugging
• dbt_error_parser — parse dbt error output into structured info
• list_projects / get_project — dbt project management
• check_budget / connection_health / query_history — operational
• list_notion_integrations / notion_search / notion_fetch_page / notion_create_page — Notion integration

Local Scripts (via plugin)

For local dbt project work, use these standalone scripts:

• scan_project.py — scan a dbt project: models, stubs, deps, hazards, work order
• validate_project.py — run dbt parse and report structural errors

Use ToolSearch to discover additional tools as needed.

Available Skills

Load these skills as needed for specialized work:

dbt Projects

• /signalpilot-dbt:dbt-workflow — Load FIRST for any dbt project. Full 5-step workflow: scan, map, validate, write, verify.
• /signalpilot-dbt:dbt-write — Load at Step 4 when writing SQL models
• /signalpilot-dbt:dbt-debugging — Load when dbt run/parse fails
• /signalpilot-dbt:dbt-date-spines — Load to fix current_date/now() hazards

SQL (load the one matching your database)

• /signalpilot-dbt:duckdb-sql — DuckDB-specific syntax and gotchas
• /signalpilot-dbt:snowflake-sql — Snowflake-specific patterns
• /signalpilot-dbt:bigquery-sql — BigQuery-specific patterns
• /signalpilot-dbt:sqlite-sql — SQLite-specific patterns

Notion Context

• /signalpilot-dbt:notion-context — Gather business context from Notion (auto-runs in dbt workflow if a Notion integration is configured in SignalPilot)

General SQL

• /signalpilot-dbt:sql-workflow — Structured query building and verification

Quick Start

For dbt projects: Load /signalpilot-dbt:dbt-workflow — it orchestrates the full lifecycle including scanning, mapping, writing, and verification.

For SQL queries: Load /signalpilot-dbt:sql-workflow + the SQL skill for your database engine.

For schema exploration: Use the MCP tools directly — schema_overview for a broad view, describe_table for column details, explore_table for sample data.