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. 'Cosine function' implies a read-only mathematical computation but doesn't specify that it returns a symbolic expression, handles input in radians, or may raise errors for invalid inputs. For a tool with zero annotation coverage, this lacks essential behavioral details like output format or error conditions.

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 just two words, which is efficient for a simple mathematical function. However, it's under-specified rather than optimally concise—it could benefit from a bit more context without becoming verbose. The structure is front-loaded but minimal.

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 low complexity (single parameter, mathematical function) and the presence of an output schema (which likely defines the return value), the description is minimally adequate. However, with no annotations and a sparse description, it lacks context on usage, behavior, and differentiation from siblings, leaving gaps in completeness for effective agent use.

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 the parameter 'expr' documented as 'Expression (in radians)' in the schema. The description adds no additional meaning beyond this, such as examples of valid expressions or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 'Cosine function' states the mathematical operation but is vague about scope and implementation. It doesn't specify that this computes the cosine of a symbolic expression using SymPy, nor does it distinguish itself from sibling trigonometric functions like sympy_sin or sympy_tan beyond the obvious name difference. The purpose is clear at a basic level but lacks specificity about the SymPy context.

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 is provided on when to use this tool versus alternatives. It doesn't mention sibling tools like sympy_sin for sine calculations or sympy_cosh for hyperbolic cosine, nor does it specify use cases such as symbolic math versus numeric computation. The description offers no context for tool selection.

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