Tool definitions not implemented in source code. The agent.py files show only class stubs with no actual tool registration, schema validation, or implementation. Tools are declared in the evaluation spec but do not exist in the codebase.
No MCP protocol implementation detected. The codebase is a standard FastAPI + Celery e-commerce application, not an MCP server. No SSE streams, HTTP handlers for MCP messages, or tool initialization protocol are present.
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Recommendations
Migrate from FastAPI + Celery to a proper MCP server library (e.g., mcp-python). Implement SSE or HTTP protocol handlers to make the server MCP-compliant and testable by MCP clients (Claude, ChatGPT, etc.).
Rewrite all tool descriptions in English, 50-200 characters, stating what the tool does, when to use it, and any side effects. Example: 'Analyzes customer sentiment from a message to determine satisfaction (positive, neutral, negative). Use before escalating complaints.'
Add comprehensive parameter descriptions with constraints. Example: 'store_id (required, 1-36 alphanumeric UUID identifying the store). Use the value from the store selection dropdown.' Replace Italian with English.
Convert enumerable parameters to formal enum constraints. For 'tone', define enum: [professional, friendly, formal]. For 'period', define enum: [last_7_days, last_30_days, last_90_days, last_year].
Document output schemas for all tools. Define response structures with field names, types, and descriptions. Example: 'Returns { sentiment: (positive|neutral|negative), confidence: (0-1), explanation: string }'.
Add error handling with recovery guidance. Example: 'If store_id not found: Error: Store U12345 not found. Available stores: [Store A, Store B]. Try again with a valid store ID or call list_stores().'
Mark destructive operations with explicit annotations: add idempotentHint: false for write operations, and include confirmation step guidance (e.g., 'Before price optimization, preview changes. Confirm pricing_optimize().').
Tool descriptions are in Italian and extremely brief (10-30 characters). LLM-optimized descriptions should be 50-200 characters in English, explaining WHAT the tool does, WHEN to use it, and any side effects.
Parameter descriptions lack actionable detail. Examples: 'ID del negozio' (5 chars, Italian) instead of 'The store ID (required, 1-36 alphanumeric characters)'. No constraints, formats, or validation guidance.
No output schemas documented. Tools return type: object with no field definitions. LLMs cannot plan downstream calls or extract structured data without knowing response field names and types.
Optional parameters lack clear guidance on when to omit vs provide. 'customer_id' is optional but its presence/absence likely changes behavior, undocumented dependencies force LLMs to guess.
No pagination support. Tools like 'inventory_analyze_trends' and 'marketing_analyze_performance' likely return large result sets (e.g., daily inventory for 90 days = 90 records) with no limit or offset parameters.
No tool annotations for destructiveness or idempotency. WRITE operations (handle_complaint, optimize, generate_description) are not marked as destructive. Agents lack signals for retry-safety.
No natural identifiers. 'store_id', 'customer_id', 'product_id' are opaque; no support for store_name, customer_email, or product_sku. Agents must perform unnecessary lookups.
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Accept human-friendly identifiers. Support both store_id and store_name; resolve names to IDs inside the tool. Same for customer_email, product_name, etc.
Implement pagination for tools returning collections. Add limit (default 20, max 100) and offset parameters. Return total_count and next_offset in response.
Add comprehensive logging and error reporting using MCP structured error format (not raw exceptions). Log tool calls, parameters, results, and failures for auditing.
Create an explicit tool registration layer with JSON Schema definitions, not inferred from function signatures. Use a tools.json or registry pattern so schemas are verifiable.
Add permission/scope declarations to each tool (e.g., 'write:pricing', 'read:inventory'). Document what user/agent roles can call each tool.
Implement idempotency for write operations. Add optional idempotency_key parameter to handle_complaint, optimize, generate_* tools to prevent duplicates on retries.