A FastAPI-based chat orchestration server that integrates LangGraph, Google Generative AI, and multiple agent frameworks (MCP, A2A) to provide a unified chat interface with tool execution capabilities.
Five tools with basic descriptions and schemas, but significant gaps in parameter documentation and error handling. Tool names follow verb_noun convention (add, subtract, multiply, divide, current_datetime), which is good. However, parameter descriptions are minimal (e.g., 'First number', 'Second number' for add/subtract/multiply), and critical error cases like division by zero are handled in code but not documented in the tool description. The current_datetime tool accepts a ToolRuntime parameter with embedded context, which is non-standard for LLM-facing tools and lacks clear documentation of what 'runtime' means. No output schemas are documented. Error handling is minimal, divide raises ValueError on zero division, but the tool description does not warn about this or guide recovery.
Add two numbers.
Get the current date and time.
Divide a by b.
Multiply two numbers.
Subtract b from a.
Parameter descriptions are generic and under 20 characters. 'First number' and 'Second number' do not explain constraints, ranges, or use cases. LLMs cannot infer whether negative numbers, decimals, or very large values are acceptable.
divide tool raises ValueError on zero division but the description does not document this error case or guide recovery. LLMs will not know to catch this or ask the user for a non-zero divisor.
current_datetime accepts a 'runtime' parameter of type ToolRuntime[Context], which is a framework-specific object. This is non-standard for LLM-facing tools and the description does not explain what this parameter is or how to populate it. LLMs cannot construct ToolRuntime objects.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 51 | 2026-07-28+ | v2 |
No output schemas are documented for any tool. LLMs do not know what fields to expect in responses, making it difficult to chain tools or extract specific data.
Tool descriptions are minimal (10-30 characters). Baseline for A+ tools is 194 chars. These descriptions lack context for when to use each tool, what they return, and any prerequisites.