sympy_product

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

No annotations exist, so the description must carry the full burden. It only says 'Compute a product' without disclosing behaviors such as whether it performs symbolic or numeric computation, what the output format is, or how bounds are handled. The existence of an output schema is not leveraged.

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 extremely concise (3 words), but it omits critical context. Conciseness is good, but not at the expense of completeness. It could be slightly longer to differentiate from siblings.

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 has 4 required parameters and an output schema, the description is too minimal. It does not explain that it computes a symbolic product over a variable from lower to upper bound, nor does it note that it is similar to sympy_sum but for multiplication.

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 with descriptions for all four parameters (expr, variable, lower, upper). The description adds no additional meaning beyond what the schema already provides. Baseline score 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 states 'Compute a product,' which is a clear verb and resource but very generic. Among siblings like sympy_product_expr and sympy_product_set, it does not differentiate what kind of product (e.g., symbolic product over a range). It is minimally adequate but lacks specificity.

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 alternatives like sympy_sum or sympy_product_expr. There is no mention of prerequisites, context, or exclusions.

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