two_unit_fraction_representations

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 the tool finds representations but does not describe output format, performance characteristics (e.g., computational limits), error handling, or whether it's deterministic. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 and front-loaded with the core purpose in a single sentence, followed by domain/category context. There is no wasted verbiage, and it efficiently communicates the essential idea without unnecessary details.

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 complexity (finding mathematical representations), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It does not address return values, error conditions, or practical constraints, making it inadequate for an agent to use the tool effectively without additional context or trial-and-error.

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 3 parameters with 0% description coverage, so the description must compensate. It only implies parameters for numerator and denominator by mentioning 'small fraction' but does not explain their roles, valid ranges, or the purpose of the 'limit' parameter. This fails to add meaningful semantics beyond the bare schema.

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 ways to represent a small fraction as sum of two unit fractions.' It specifies the verb ('find'), resource ('ways'), and scope ('small fraction'), and includes domain/category context. However, it does not explicitly differentiate from sibling tools like 'egyptian_fraction_decomposition' or 'unit_fraction_sum', which are related but not identical, leaving room for ambiguity.

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 and category but does not specify use cases, prerequisites, or exclusions. For example, it does not clarify what constitutes a 'small fraction' or when to choose this over other Egyptian fraction tools in the sibling list.

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