mcp-sympy

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

No annotations are provided, so the description must fully disclose behavioral traits. 'Cube root' gives no information about the tool's behavior, such as whether it computes symbolic or numeric results, handles errors, or requires specific input formats. It fails to compensate for the lack of annotations, offering no operational insights.

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 extremely concise with 'Cube root.', which is front-loaded and wastes no words. While it lacks substance, it is structurally efficient, earning a high score for brevity and clarity in its minimal form.

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 mathematical nature, no annotations, and an output schema (which reduces the need to describe return values), the description is incomplete. It fails to provide essential context like usage scenarios, behavioral details, or differentiation from siblings, making it inadequate for effective tool invocation 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?

The input schema has 100% description coverage, with the 'expr' parameter documented as 'Expression'. The description adds no additional meaning beyond this, such as examples or constraints. Since the schema is fully descriptive, the baseline score of 3 is appropriate, as the description does not enhance or detract from parameter understanding.

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 'Cube root' is a tautology that merely restates the tool name 'sympy_cbrt' without specifying the action or resource. It lacks a clear verb (e.g., 'compute' or 'evaluate') and does not distinguish this tool from its many siblings, such as 'sympy_sqrt' for square roots or other mathematical functions. This provides minimal guidance to an AI agent.

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 offers no guidance on when to use this tool versus alternatives. With numerous sibling tools for mathematical operations (e.g., 'sympy_sqrt', 'sympy_root'), there is no indication of context, prerequisites, or comparisons. This leaves the agent without direction for tool selection.

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