expand_expression

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

No annotations are provided, so the description carries the burden. It is a pure, side-effect-free symbolic transform, and the example conveys that output shape, but the description never states that it performs no mutation, nor how it handles non-polynomial or unparseable input.

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?

A single front-loaded sentence with an embedded example; nothing wasted and the purpose is immediately clear.

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?

For a single-parameter pure-math tool with an output schema present, the description covers the essentials; return semantics need not be restated. It is only slightly thin on input-format edge 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?

One parameter with 0% schema description coverage, so the description must compensate. The inline example '(x + 1)**2' does illustrate the expected string syntax of the expression argument, which is genuinely useful, but it stops short of stating syntax rules or error conditions.

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?

States a specific verb (expand) and resource (symbolic expression), with a concrete input→output example that makes the operation unambiguous. It does not, however, differentiate itself from close siblings like simplify_expression or factor_expression, leaving the agent to infer the boundary.

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?

Usage is implied by the example: use it when you want a product/power form rewritten as a sum of terms. There is no explicit when-to-use statement, no mention of when to prefer simplify_expression or factor_expression, and no prerequisites noted.

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