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. 'Add two matrices' implies a mathematical operation but doesn't specify critical behaviors: whether it validates input formats (e.g., string parsing for matrices), handles errors (e.g., dimension mismatches), or requires specific permissions. For a tool with no annotations, 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 'Add two matrices' is extremely concise—three words that directly convey the core action. It's front-loaded with zero wasted words, making it easy for an agent to parse quickly. Every word earns its place by specifying the operation and resource.

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 (simple addition), high schema coverage (100%), and presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks context on usage guidelines and behavioral traits, which are important for a tool with no annotations. It meets basic needs but has clear gaps in guidance.

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 ('First matrix string', 'Second matrix string'), so the schema does the heavy lifting. The description adds no additional meaning beyond implying two inputs are required. Baseline 3 is appropriate as the schema provides adequate parameter documentation without extra value from the description.

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 'Add two matrices' clearly states the verb ('Add') and resource ('two matrices'), making the purpose immediately understandable. It distinguishes this tool from siblings like sympy_matrix_multiply or sympy_matrix_transpose by specifying the operation. However, it doesn't explicitly differentiate from sympy_symbolic_add, which might handle symbolic addition differently, keeping it from a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., matrix dimensions must match), when not to use it (e.g., for scalar addition), or direct alternatives like sympy_symbolic_add for symbolic operations. This lack of context leaves the agent without usage direction.

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