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 for behavioral disclosure. It mentions nothing about what the tool returns (though an output schema exists), whether it's read-only or mutating, error conditions, or performance characteristics. The phrase 'match' is vague and doesn't clarify behavioral traits.

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 four words. While this brevity reflects under-specification rather than effective communication, it technically meets conciseness criteria with zero wasted words.

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 of symbolic mathematics tools, zero annotations, 0% schema coverage, and many sibling tools, the description is completely inadequate. It fails to explain purpose, usage, parameters, or behavior, leaving the agent with insufficient information to use the tool correctly despite the existence of an output schema.

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 0%, meaning neither parameter (expr, pattern) has documentation in the schema. The description adds no information about what these parameters represent, their expected formats (e.g., symbolic expressions as strings), or examples of valid inputs.

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 'Match expression to pattern' restates the tool name 'sympy_match' in slightly different words, making it tautological. It doesn't specify what kind of matching occurs (e.g., pattern matching for symbolic mathematics), what domain this applies to (SymPy symbolic algebra), or how it differs from sibling tools like sympy_eq or sympy_subs.

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 about when to use this tool versus alternatives. With many sibling tools for symbolic manipulation (e.g., sympy_eq for equality testing, sympy_subs for substitution), the description offers no context about appropriate use cases or distinctions.

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