Production-grade Python framework for building, orchestrating, and deploying multi-agent LLM systems with graph-based workflows, durable state, native MCP support, and provider-agnostic LLM integration
Single tool 'get_weather' has critical definition gaps. Description is present but minimal (34 chars, below baseline 194). Input schema visible but incomplete: 'location' param has description, but 'user' param marked as 'object' with no field definitions and noted as 'excluded from tool definition', contradictory and non-functional. No output schema documented. No error handling guidance. Tool appears to be a mock/test fixture (file: agentflow/qa/testing/mock_tools.py), not production code. This is a test harness, not a real MCP server implementation.
Get the weather for a specific location
Output schema completely undocumented. No return type, fields, or structure defined for get_weather response.
Input schema malformed: 'user' parameter is type 'object' with no field definitions and marked 'excluded from tool definition', contradictory and non-functional.
Tool description is 34 characters ('Get the weather for a specific location'), below baseline 194 chars. Lacks context on when to use, what it returns, or prerequisites.
No error handling guidance. No documentation of failure modes, retryability, or recovery steps for invalid locations or API failures.
Tool is located in test/mock directory (agentflow/qa/testing/mock_tools.py), indicating this is a test fixture, not a production MCP server implementation.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 47 | 2026-07-28+ | v2 |