mcp-sympy

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('compute union') but does not describe key behaviors like input format expectations (e.g., string representation of sets), error handling, or output characteristics. This leaves significant gaps in understanding how the tool operates beyond its basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core function without unnecessary elaboration, which is ideal for quick comprehension in a list of many sibling tools.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (basic set operation), 100% schema description coverage, and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks details on behavioral aspects like input formatting or error cases, which could be important for correct usage, making it incomplete for full contextual understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear parameter names and descriptions ('First set', 'Second set'). The description adds no additional semantic information beyond what the schema provides, such as examples of valid set representations or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately documents the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('compute') and resource ('union of two sets'), making the purpose immediately understandable. However, it does not explicitly differentiate from sibling tools like 'sympy_intersection' or 'sympy_complement', which are related set operations, leaving room for potential confusion in selection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as 'sympy_intersection' for set intersection or 'sympy_complement' for set complement. It lacks context about prerequisites, typical use cases, or comparisons with sibling tools, offering minimal assistance in tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.