evaluate

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

No annotations exist, and the description does not disclose any behavioral traits such as side effects, performance considerations, or error handling. The tool is presented as a black box.

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 concise, consisting of one declarative sentence followed by examples. It front-loads the core purpose and is free of unnecessary words, though the examples could be more systematically structured.

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?

There is no output schema, yet the description does not mention return types or format. The nested 'scope' object lacks explanation of structure. Given the complexity and multiple siblings, the description is insufficient for an agent to fully understand the tool's capabilities and boundaries.

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% coverage, describing both parameters. The description adds a concrete example for 'scope', clarifying its usage. However, no additional semantics are provided for 'expression' beyond what the schema offers.

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 states 'Evaluate a mathematical expression' and lists examples covering arithmetic, calculus, matrices, etc. However, sibling tools like 'derivative' and 'matrix_operations' overlap with the claimed capabilities, creating ambiguity about when to use this tool versus more specific tools.

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 provided on when to use this tool versus siblings. There are no conditions, limitations, or examples of appropriate use cases, leaving the agent to infer from context.

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