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 mentions the output is an 'unevaluated sum (Sum object)', which hints at symbolic rather than numeric computation, but lacks details on permissions, error handling, or performance implications. For a tool with no annotations, this is insufficient behavioral disclosure.

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 directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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 moderate complexity (3 required parameters) and the presence of an output schema (which handles return values), the description is mostly complete. However, it lacks guidance on usage versus siblings and behavioral details, which are minor gaps in an otherwise adequate 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 schema description coverage is 100%, so the schema already documents all three parameters (expr, variable, bounds) with clear descriptions. The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline score of 3 for high schema coverage.

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 action ('Compute') and the resource ('unevaluated sum (Sum object)'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'sympy_sum' (which might compute evaluated sums) or 'sympy_product' (for products), leaving some ambiguity about when to choose this specific summation tool.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools (e.g., 'sympy_sum' for evaluated sums or 'sympy_integral' for integrals) or specify contexts like symbolic versus numeric computation, leaving the agent without usage direction.

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