Symbolic Algebra MCP Server

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

With no annotations provided, the description carries the full burden. It discloses that the tool 'stores' the function (implying state mutation) and returns the function name, but lacks details on permissions, error conditions, or side effects. The example adds some behavioral context, but key aspects like persistence scope or limitations are missing.

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 appropriately sized and front-loaded, with the core purpose stated first, followed by usage context, an example, and return information. Each sentence adds value, though the structure could be slightly more streamlined (e.g., merging the first two sentences).

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 no annotations, no output schema, and a single parameter with 0% schema coverage, the description is moderately complete. It covers the basic purpose, parameter usage, and return value, but lacks details on error handling, state management, or integration with sibling tools, leaving gaps for a mutation tool in a mathematical context.

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 0% description coverage (no parameter descriptions), but the tool description compensates well. It explains the 'func_name' parameter's purpose ('Takes a function name and creates a SymPy Function object') and provides an example ('{func_name: "f"} will create the function f(x), f(t), etc.'), adding meaningful semantics beyond the bare schema.

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 clearly states the tool's purpose: 'Introduces a SymPy function variable and stores it' and 'creates a SymPy Function object for use in defining differential equations.' It specifies the verb ('introduces', 'creates') and resource ('SymPy function variable/object'), though it doesn't explicitly differentiate from sibling tools like 'introduce_expression' or 'intro_many'.

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 minimal usage guidance, mentioning it's 'for use in defining differential equations' but doesn't specify when to use this tool versus alternatives like 'introduce_expression' or 'intro_many'. No explicit when-not-to-use or prerequisite information is given.

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