barwise-modeling

Build, validate, verbalize, and export ORM 2 conceptual models in .orm.yaml files.

Updated Feb 17, 2026
One-click install
npx skills add https://github.com/semantic-praxis/barwise --skill barwise-modeling-semantic-praxis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: barwise-modeling
Source: https://github.com/semantic-praxis/barwise/tree/main/.claude/skills/barwise-modeling
Command: npx skills add https://github.com/semantic-praxis/barwise --skill barwise-modeling-semantic-praxis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Object-Role Modeling requires a disciplined workflow from business-domain transcripts to validated conceptual schemas, and doing this by hand across tools is error-prone. This Skill provides the modeling workflow and tool-usage rules for the barwise toolkit so models are captured, validated, verbalized, reviewed, and exported consistently. ## Core Features & Use Cases - Guided Modeling Workflow: Follows a six-step pipeline (capture, extract, validate, verbalize, review, export) using the barwise MCP server, CLI, or VS Code extension. - Import and Export: Drafts models from transcripts with import_transcript, converts DDL/OpenAPI/code with import_model, and exports finished models to DDL or OpenAPI. - Context Hygiene and Delegation: Routes heavy operations like transcript extraction and full model review to sub-agents so large inputs never flood the main context window. - Use Case: Given a stakeholder interview transcript about an order-management domain, use this Skill to draft an .orm.yaml model, validate its constraints, verbalize the fact readings for review, and export DDL for the database team. ## Quick Start Use the barwise-modeling skill to import this domain transcript into an ORM model, validate it, and verbalize the fact readings.

Frequently Asked Questions about barwise-modeling

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

FAQPage Schema
How do I create an ORM model from a business transcript?▼

Use the import_transcript tool from the barwise MCP server to draft an .orm.yaml model from a domain transcript. For large transcripts, delegate to the barwise-transcript-extractor sub-agent so the bulk content stays out of the main context window.

How do I convert DDL or OpenAPI specs into an ORM model?▼

Use the import_model tool, which converts DDL, OpenAPI, or code into a draft ORM model. After importing, run validate_model to resolve structural errors before verbalizing or exporting.

What tools does the barwise toolkit provide for ORM modeling?▼

Barwise ships as an MCP server (barwise-mcp) with tools, resources, and prompts, a barwise CLI, and a VS Code extension, all backed by the same @barwise/core library. Models are stored as .orm.yaml files.

Can I export an ORM model to a database schema?▼

Yes, the export_model tool exports a validated model to formats including DDL and OpenAPI. Export only after the model passes validate_model and has been reviewed with review_model for semantic quality.

Why delegate model review to a sub-agent?▼

Full model review consumes large inputs and emits large outputs, which would flood the main context window. The barwise-model-reviewer sub-agent runs in its own context and returns only a short summary of findings.