egyptian_expansion_lengths

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 calculates expansion lengths but doesn't explain what 'length' means (e.g., number of terms), whether it's a deterministic algorithm, if there are computational limits, or what the output format is. For a tool with zero annotation coverage, this is a significant gap in 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 extremely concise—a single sentence that directly states the tool's purpose, followed by domain and category in parentheses. There is no wasted language, and the information is front-loaded. This efficiency makes it easy to parse, though it may lack necessary 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 tool's complexity (involving Egyptian fraction expansions), lack of annotations, no output schema, and low parameter coverage, the description is insufficient. It doesn't explain the algorithm, output format, or behavioral traits, making it incomplete for effective use by an AI agent. More context is needed to understand how to interpret results or handle 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?

The input schema has one parameter 'max_n' with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'max_n' represents (e.g., maximum denominator to compute up to), its valid range, or how it affects the calculation. With low schema coverage, the description fails to compensate, leaving the parameter undocumented.

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: 'Calculate the length of Egyptian fraction expansion for fractions 1/n.' It specifies the verb ('calculate'), resource ('length of Egyptian fraction expansion'), and domain ('fractions 1/n'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'egyptian_fraction_decomposition' or 'shortest_egyptian_fraction', which would be needed for a perfect score.

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. While it mentions the domain ('arithmetic') and category ('egyptian_fractions'), it doesn't specify use cases, prerequisites, or comparisons with sibling tools like 'egyptian_fraction_decomposition' or 'shortest_egyptian_fraction'. This leaves the agent without clear direction on tool selection.

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