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setup-dev-context

Configure AI Analyst with a YAML dev-context file for SQL and schema conventions.

16|7|Updated Apr 1, 2026
Search Tags:#development#dbt#warehouse#team-integration#dev-context#sql-conventions
One-click install
npx skills add https://github.com/ai-analyst-lab/ai-analyst-plus --skill setup-dev-context
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: setup-dev-context
Source: https://github.com/ai-analyst-lab/ai-analyst-plus/tree/main/.claude/skills/setup-dev-context
Command: npx skills add https://github.com/ai-analyst-lab/ai-analyst-plus --skill setup-dev-context

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Configure AI Analyst to understand your development environment and codebase structure. Use this skill when developers need to integrate AI Analyst into their workflow, or when questions arise about database configuration, SQL conventions, schema naming patterns, dbt integration, warehouse connections, or team-specific data practices.

Core Features & Use Cases

  • Collects repository type, data layer details, SQL conventions, integration points, and file conventions through a guided interview.
  • Enforces a strict sequence of steps to avoid incomplete configuration.
  • Generates and saves .knowledge/user/dev-context.yaml with codebase, data_layer, sql_conventions, integration, and file_conventions.
  • Updates overall setup-state.yaml to reflect progress.

Quick Start

Run the developer context setup flow with /setup-dev-context to configure your team's AI Analyst bindings.

Frequently Asked Questions about setup-dev-context

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

FAQPage Schema
How do I configure AI Analyst to understand my dbt repository and data warehouse setup?▼

To configure AI Analyst for your dbt repository and data warehouse, run a guided interview that collects codebase structure, schema prefixes, and team conventions, generating a dev-context.yaml file for tailored SQL generation.

How do I set up SQL conventions and schema naming patterns for AI-generated queries?▼

Setting up SQL conventions and schema naming patterns involves defining rules in a dev-context.yaml configuration file, ensuring AI Analyst adapts SQL generation to respect your team's specific data practices and integration points.

Can I integrate AI Analyst into an existing team development workflow?▼

Yes, you can integrate AI Analyst into team development workflows by applying the configuration during team onboarding, which tailors schema awareness and data layer integration to match your current stack and file conventions.

What is the best way to document codebase structure and data layer details for an AI analyst?▼

The best way to document codebase structure and data layer details is using a lightweight YAML dev-context config, which captures repository type, models path, and integration mode to provide full stack awareness.

Do I need a specific file format to store development environment configuration for AI tools?▼

You need a lightweight YAML file located at .knowledge/user/dev-context.yaml to store development environment configuration, including schema_prefix, models_path, sql_conventions, and integration mode for AI tools.

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