[PUBLIC READ/WRITE] Execute mathematical expression, symbolic polynomial evaluation, derivatives, or statistical functions.
| Name | Required | Description | Default |
|---|---|---|---|
| variables | No | Variable values map (e.g., {"x": 4, "y": 1.57}) | |
| expression | Yes | Mathematical expression (e.g., "3*x^2 + 2*x - 5", "sqrt(x) + sin(y)") |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full behavioral burden. It includes a terse '[PUBLIC READ/WRITE]' tag indicating access level, but does not explain what 'WRITE' means for a math tool, whether anything is persisted, permission requirements, or expected response behavior.
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 front-loaded sentence with no filler. It is appropriately concise, though the bracketed access tag is not integrated into a fuller structure.
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?
The purpose and supported operations are clear, and the schema fully documents parameters. However, with no annotations and no output schema, the description does not describe return values, side effects, or operation-specific behavior, leaving meaningful gaps for an agent.
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%, so both parameters and the nested variables object are already documented in the schema. The description adds no parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate.
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 uses a clear verb ('Execute') and resource ('mathematical expression') and lists supported capabilities such as symbolic polynomial evaluation, derivatives, and statistical functions. However, it does not differentiate this tool from nearby siblings like execute_cell_math or solve_symbolic_matrix.
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 given on when to use this tool versus alternatives such as execute_cell_math or solve_symbolic_matrix. The description states capabilities but provides no context, exclusions, or decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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