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. It states the tool creates an unevaluated object, which implies it's a symbolic operation rather than a computational one, but doesn't disclose behavioral traits like whether it validates inputs, returns errors for invalid expressions, or requires specific formatting. For a tool with no annotation coverage, this is insufficient.

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, efficient sentence that front-loads the key information ('Create an Integral object') with a crucial qualifier ('unevaluated'). There is no wasted verbiage, and it's appropriately sized for the tool's complexity.

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 that there's an output schema (implied by 'Has output schema: true'), the description doesn't need to explain return values. However, with no annotations and a symbolic operation tool, it lacks context about error handling, symbolic vs. numeric behavior, or differentiation from siblings. It's minimally adequate but leaves gaps in understanding the tool's full context.

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 documentation for 'expr' and 'variable'. The description adds no additional parameter semantics beyond what the schema provides, such as examples of valid expressions or variable naming conventions. With high schema coverage, the baseline score of 3 is appropriate.

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 ('Create') and resource ('Integral object') with the qualifier 'unevaluated', which distinguishes it from evaluation tools. However, it doesn't explicitly differentiate from sibling tools like 'sympy_integrate' (which likely performs actual integration), leaving some ambiguity about when to use this versus that sibling.

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. It doesn't mention the sibling 'sympy_integrate' or explain that this creates an unevaluated symbolic representation rather than computing a result. There's no context about prerequisites or typical use cases.

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