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. 'Create Float.' gives no information about the tool's behavior: it doesn't describe what the tool does with the input (e.g., parses a string to a Float object), whether it has side effects, error handling, or output format. The description is too vague to inform an agent about how the tool operates beyond its name.

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 overly concise to the point of being underspecified. While it's only two words, it lacks essential information that would make it useful. Conciseness should not come at the expense of clarity; here, the brevity results in a description that doesn't help an agent understand or use the tool effectively.

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 complexity implied by sibling tools (mathematical/symbolic computation) and the lack of annotations, the description is incomplete. It doesn't cover the tool's purpose, usage, parameters, or behavior. Although an output schema exists, the description doesn't leverage it to provide context (e.g., hinting at what the Float object might be used for). For a tool in a rich mathematical library, this description is inadequate.

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 one parameter 'n' with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'n' represents (e.g., a numeric string or expression), its expected format, or how it's used to create a Float. With low schema coverage, the description fails to compensate, leaving the parameter's meaning and usage completely undocumented.

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 'Create Float.' is a tautology that restates the tool name 'sympy_float' without adding meaningful context. It doesn't specify what resource is being created (e.g., a symbolic Float object from a string input) or distinguish it from sibling tools like 'sympy_rational' or 'sympy_integer', which likely create other numeric types. The verb 'Create' is generic and lacks specificity about the mathematical operation.

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 sibling tools (e.g., 'sympy_rational' for rational numbers or 'sympy_integer' for integers) or specify contexts where creating a Float is appropriate (e.g., for decimal inputs or symbolic computations requiring floating-point precision). There's no indication of prerequisites, constraints, 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.