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. 'Factorial.' reveals nothing about the tool's behavior - it doesn't indicate whether this is a read-only computation, whether it has side effects, what happens with invalid inputs, performance characteristics, or what the output looks like. For a computational tool with zero annotation coverage, this complete lack of behavioral information is inadequate.

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?

While technically concise with just one word, this represents under-specification rather than effective conciseness. The single word 'Factorial.' fails to provide the necessary information that should be included in a tool description. True conciseness balances brevity with completeness, which this description does not achieve.

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 that this is a mathematical computation tool with no annotations but with a complete input schema and an output schema (per context signals), the description is insufficient. While the output schema may document return values, the description should still explain what the tool does, when to use it, and basic behavioral context. The single-word description fails to provide the minimum viable information needed for an AI agent to understand and appropriately use this tool.

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 single parameter 'n' clearly documented as a 'Non-negative integer' string. The description adds no parameter information beyond what's already in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no parameter information in the description, which applies here.

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 'Factorial.' is a tautology that merely restates the tool name without adding meaningful context. It doesn't specify what the tool actually does (e.g., 'Compute the factorial of a non-negative integer'), nor does it distinguish this mathematical function from the many other mathematical operations in the sibling tools list. While the name itself suggests a mathematical operation, the description fails to clarify the purpose beyond what's already implied by the name.

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 provides absolutely no guidance about when to use this tool versus alternatives. With dozens of sibling mathematical tools (like sympy_gamma, sympy_binomial, sympy_gcd), there's no indication of when factorial computation is appropriate versus other mathematical operations. The description doesn't mention prerequisites, constraints, or typical use cases for factorial calculations.

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