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. It states the action ('solve') but doesn't describe traits like error handling, convergence criteria, output format, or performance implications. For a numerical solver with no annotation coverage, this is a significant gap in transparency.

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 zero waste. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse quickly without unnecessary elaboration.

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, the description is minimally adequate. However, with no annotations and a vague purpose, it lacks completeness in explaining behavioral traits and usage context. The output schema mitigates some gaps, but overall it's borderline viable.

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 clear parameter descriptions in the schema. The description adds no additional meaning beyond implying numerical solving, which is already suggested by the tool name 'nsolve'. Baseline 3 is appropriate as the schema does the heavy lifting, though the description doesn't compensate with extra context like equation format examples.

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 'Numerically solve an equation' states a clear verb ('solve') and resource ('equation'), but it's vague about scope and method. It doesn't distinguish from sibling tools like 'sympy_solve' or 'sympy_solveset', which likely offer alternative solving approaches. The purpose is understandable but lacks specificity about numerical vs. symbolic solving.

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 is provided. The description doesn't mention prerequisites, such as when numerical methods are preferred over symbolic ones, or refer to sibling tools like 'sympy_solve'. This leaves the agent without context for tool selection among many mathematical functions.

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