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 evaluation to floating point but doesn't disclose behavioral traits such as precision handling (default digits=15), error conditions (e.g., invalid expressions), or output format. This leaves significant gaps for a tool that performs computation.

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, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core purpose without unnecessary elaboration, 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 has an output schema (which handles return values) and 100% schema coverage for inputs, the description is minimally adequate. However, with no annotations and a computational tool, it lacks context on behavior, errors, or sibling differentiation, leaving room for improvement despite the structured support.

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?

Schema description coverage is 100%, with parameters 'expr' and 'n' fully documented in the schema. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain expression syntax or digit implications), so it meets the baseline of 3 for high schema coverage without extra value.

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 'Evaluate expression to floating point' states the basic action (evaluate) and target (floating point), but it's vague about what kind of expression it handles (mathematical? symbolic?) and doesn't distinguish it from sibling tools like 'sympy_float' or 'sympy_evaluate' which might have overlapping purposes. It's functional but lacks specificity.

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?

There is no guidance on when to use this tool versus alternatives like 'sympy_float' or 'sympy_evaluate' from the sibling list, nor does it mention any prerequisites or context for usage. The description provides no usage instructions beyond the basic action.

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