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Schema Polish refines and improves an existing schema — cleaning up naming conventions, structure, types, and consistency without changing its core definition. This feature helps make your schemas more understandable and usable for both humans and AI models.

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How It Works

Schema Polish uses a two-phase approach:
  1. Phase 1: Pilot Optimization: The system samples a subset of your schemas and proposes improvements. You can accept, reject, or provide feedback on each change.
  2. Phase 2: Large-Scale Generation with Online Monitoring: After Phase 1, the refined patterns are applied to all remaining schemas for final confirmation.

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Parameters

Either schema_file or mcp_server_url must be provided. This feature uses the standard chatbot interaction flow. Describe what schema refinement you want in natural language, and the CLI guides you through parameter collection and confirmation.

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Phase 1: Pilot Optimization — Review iteration diff

After refinement runs, the CLI displays a side-by-side comparison for each schema change.
Side-by-side diff showing schema changes during pilot optimization review

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Accept or reject changes

Use the keyboard shortcuts to review each change:
  • Press Enter to accept the current modification
  • Press r to reject and provide feedback
  • Press R to reject all remaining modifications
Your feedback is collected and used for the next iteration to improve results.

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Phase 2: Large-Scale Generation — Final confirmation

After Phase 1 iterations complete, Phase 2 presents all schemas for final confirmation: In Phase 2, you can still accept or reject each change, but no feedback is collected for further iteration.
Phase 2 final confirmation view for all schema changes

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Completion

Once all schemas are confirmed:
Schema polish completion summary showing output path

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Output

After a run completes, results are saved under outputs/ as a new run directory, for example:
  • outputs/refined_schema_<run_id>/
Inside the run directory:
  • refined_schema.json or refined_schema.yaml - The refined schema (matches your input format)
  • metadata.json - Run metadata (task type, parameters, primary files, timestamps)
The viewer can browse and render these outputs.

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Using an MCP Server

You can also refine schemas from an MCP server instead of a local file. Simply mention the MCP server URL in your conversation:
The system will automatically use the MCP server as the schema source.

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Using /execute

You can also run schema-polish non-interactively via /execute with a YAML config. Prerequisites
  • You have a YAML configuration file available.
  • You provide a schema source (schema_file or mcp_server_url).