mcp-sympy

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

No annotations are provided, so the description carries full burden. It mentions 'differentiate' but does not disclose behavioral traits such as error handling (e.g., invalid expressions), computational complexity, or output format. This is a significant gap for a tool with no annotation coverage.

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 with no wasted words. It is appropriately sized for a simple tool, though it could be more front-loaded with additional context without losing conciseness.

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 3 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, with no annotations and many sibling tools, it lacks completeness in guiding usage and behavior, making it only marginally sufficient for an AI agent.

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%, so the schema fully documents parameters (expr, variable, order). The description adds no meaning beyond the schema, as it does not explain parameter interactions or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Differentiate an expression' states the verb ('differentiate') and resource ('expression'), but is vague about scope and does not distinguish from siblings like 'sympy_derivative' or 'sympy_integrate'. It lacks specificity about mathematical differentiation versus other operations.

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 on when to use this tool versus alternatives like 'sympy_derivative' or 'sympy_integrate' is provided. The description implies usage for differentiation but offers no context, prerequisites, or exclusions, leaving the agent to infer based on tool names alone.

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