goldbach_pairs

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on performance (e.g., computational limits for large inputs), error handling (e.g., what happens if 'n' is odd), or output format. For a tool with no annotations, this is a significant gap in transparency.

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 highly concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. The additional domain and category information in parentheses is brief and relevant, adding context without unnecessary elaboration. Every part of the description earns its place efficiently.

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's complexity (involving number theory computations), lack of annotations, no output schema, and low schema description coverage, the description is insufficient. It does not cover behavioral aspects like performance limits, error conditions, or what the output looks like (e.g., list of pairs). For a tool with these gaps, more detail is needed to be complete.

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 0% description coverage, with one parameter 'n' of type integer. The description adds meaning by specifying that 'n' must be an even number, which is crucial context not in the schema. However, it does not explain the range or constraints (e.g., minimum value, handling of non-integers), leaving some ambiguity. Given the low schema coverage, this partial compensation earns a baseline score.

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's purpose: 'Find all Goldbach pairs for an even number.' It specifies the verb ('Find'), resource ('Goldbach pairs'), and constraint ('for an even number'). However, it does not explicitly differentiate from sibling tools like 'goldbach_conjecture_check', which might have overlapping functionality but isn't directly distinguished here.

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 provides no guidance on when to use this tool versus alternatives. It mentions the domain ('arithmetic') and category ('additive_number_theory'), but does not specify prerequisites, when-not-to-use scenarios, or refer to sibling tools like 'goldbach_conjecture_check' for comparison. This leaves the agent without clear usage context.

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