EcoSupplyAI exhibits significant quality gaps across definition rubric dimensions. Tool definitions are present but lack rigor. Schema completeness is inconsistent: tools 1-3, 5 have basic JSON schemas with required fields and property types, but lack descriptions for most parameters (e.g., search_suppliers has 'query', 'country', 'industry' properties but only 'query' has a description). Parameters 'country' and 'industry' are completely undescribed. Tools 4, 6 show duplicate tool naming (both 'search_regulations') suggesting either registration errors or poor tool hygiene. Tool descriptions are present but brief (avg ~70 chars), below the 194-char production baseline. No evidence of output schema documentation, what fields does get_supplier_details return? Are they paginated? No description answers these questions. Error handling is absent from all visible definitions, there is no recovery guidance, no error categorization. The tool generate_report is marked WRITE but lacks confirmation/dry-run pattern. Tool naming shows minor issues: tools 4 and 6 are duplicates; 'search_regulations' appears twice with slightly different descriptions (one mentions 'EU sustainability regulations', the other 'EU sustainability regulations and compliance documents'). No parameter descriptions for most tools prevent LLMs from inferring valid input ranges or formats. Risk classification is present (READ_ONLY vs WRITE) but not integrated into descriptions as required by pattern:command-tool.

• URGENT: Remove duplicate 'search_regulations' tool. Keep one canonical definition with complete description and parameter docs. Consider renaming to 'search_eu_regulations' for clarity.
• Add full parameter descriptions to ALL tools. Every parameter must explain: (1) what it controls, (2) expected format/range, (3) valid values (as enum if constrained). Example: supplier_id → 'Supplier ID (format: SUP-XXXXX, 5-6 digits)'.
• Document output schemas for every tool. In tool description or as a separate schema field, specify: What fields are returned? What types? What IDs are included for chaining? Example: 'Returns {supplier_id, name, country, industry, status, esg_score, risk_level, date_updated}'.
• Add error handling guidance to descriptions. State what errors are possible and what the LLM should do. Example: 'If supplier_id not found, returns 404 with list of available suppliers. Retry with correct ID or call search_suppliers() to find it.'
• Add enum constraints to parameters with fixed options: generate_report report_type → enum: ['quarterly', 'annual']. forecast_emissions months_ahead → type: integer, minimum: 1, maximum: 36.
• Consolidate overlapping tools: Merge search_suppliers and search_supplier_database into one. Keep calculate_esg_score and get_esg_score only if they return materially different data (e.g., one includes sub-scores, one returns single number). If identical, delete one.
• Remove example values from descriptions (e.g., 'SUP-001'). Use format/pattern constraints in schema instead. Description should say 'Supplier ID format: 3 letters + dash + 4 digits' not 'e.g., SUP-001'.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry