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. It only states what the tool does at a high level ('Logarithm with specified base') but doesn't disclose behavioral traits like: whether it returns symbolic or numeric results, error handling for invalid inputs, domain restrictions, or output format. For a mathematical tool with no annotation coverage, this is a significant gap.

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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple mathematical function and front-loads the core purpose immediately.

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 simplicity (2 parameters, 100% schema coverage, output schema exists), the description is reasonably complete. The output schema will handle return value documentation, so the description doesn't need to explain results. However, it lacks behavioral context that would be helpful for an AI agent (e.g., symbolic vs. numeric computation, error cases).

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 both parameters ('expr' and 'base') having adequate schema descriptions. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain what constitutes valid expressions or bases, or provide examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 'Logarithm with specified base' clearly states the verb (logarithm) and the key resource (base specification). It distinguishes from the sibling 'sympy_log' (which likely computes natural log) by explicitly mentioning the base parameter. However, it doesn't specify what mathematical operation is being performed on the expression parameter beyond 'logarithm'.

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 like 'sympy_log' (natural log) or other mathematical functions. It doesn't mention prerequisites, error conditions, or typical use cases. The agent must infer usage from the tool name and parameters alone.

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