compute

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It accurately indicates a computational tool via examples, but does not describe potential limitations, output formatting behaviors, or error handling. It does not contradict any annotations, but lacks richer behavioral context.

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 focused paragraph that front-loads the core purpose and then provides illustrative examples. While somewhat long due to the many examples, each example adds practical value for understanding supported syntax, so it earns its place.

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?

With no output schema and no annotations, the description covers the purpose and input syntax well but omits details about return values, output structure (unless using 'format' parameter), and situational guidance relative to siblings. It is adequate for invoking the tool but leaves some gaps in full 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?

Schema description coverage is 100%, so the baseline is 3. The description enriches the 'problem' parameter with detailed CAS-style examples (e.g., 'solve(x^2-4=0, x)', 'det([[1,2],[3,4]])'), which adds meaningful guidance beyond the schema. Other parameters are well-documented in the schema itself.

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 solves math problems across many domains and provides explicit CAS-style examples. It distinguishes itself from siblings primarily through its focus on computation, but does not explicitly contrast with 'plot' or 'verify'.

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 implies usage for math problem-solving through examples, but it does not provide explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or contexts where 'verify' or 'plot' might be more appropriate, leaving the agent to infer usage.

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