calendar_approximations

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 does not describe how it behaves—e.g., whether it returns a list of approximations, a single best match, error handling, or computational limits. For a tool with no annotations, this lack of behavioral detail is a notable shortfall.

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—two brief sentences that directly state the tool's function and domain/category without any fluff. It is front-loaded with the core purpose, making it efficient and easy to parse, though this conciseness comes at the cost of detail.

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 (mathematical approximation tool), lack of annotations, no output schema, and undocumented parameters, the description is incomplete. It does not explain what the tool returns, how approximations are calculated, or any limitations, making it insufficient for effective use by an AI agent.

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 ('year_length') with 0% description coverage, and the tool description does not mention parameters at all. It fails to explain what 'year_length' represents (e.g., in days, decimal years) or its expected format, leaving the parameter undocumented. This is inadequate given the low schema coverage.

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 calendar approximations using continued fractions.' It specifies the verb ('Find'), resource ('calendar approximations'), and method ('using continued fractions'), which is specific and informative. However, it does not distinguish this tool from its many siblings, as the sibling list includes numerous mathematical tools but no obvious alternatives for calendar approximations.

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 ('continued_fractions'), which implies context but does not specify use cases, prerequisites, or exclusions. With many sibling tools available, the lack of comparative guidance is a significant gap.

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