DataMorph provides 5 tools with basic schemas and descriptions, but falls short of production quality. Tool names are clear action verbs (convert, batch, schema, validate, formats), but descriptions lack depth and parameter documentation is inconsistent. Input schemas are present but many parameters lack descriptions or type constraints. No output schemas documented. Error handling guidance is absent. The server is STDIO-only, which caps protocol readiness at 50 regardless of definition quality.

• Document output schemas for all tools. E.g., convert should return {rows_written: int, input_format: string, output_format: string, errors: [string]}. This enables LLMs to chain tools and extract IDs/references.
• Expand tool descriptions to 100-200 characters. Include WHEN to use each tool and what it returns. E.g., 'Convert a single file between formats (CSV, JSON, Parquet, YAML, Avro). Use batch() for multiple files. Returns row count and format names.'
• Add descriptions to all parameters. E.g., 'recursive: boolean, if true, search subdirectories recursively; if false, only search the top-level directory (default: false)'.
• Add error handling guidance. E.g., 'If conversion fails with "unsupported format", call formats() to see available options. If file not found, check the path and permissions.'
• Add a dry-run or confirmation parameter to convert and batch. E.g., 'dry_run: boolean, if true, validate without writing files (default: false)'. This prevents accidental data loss.