rational_to_cf

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

No annotations are provided, so the description carries the full burden. It states the conversion action but lacks behavioral details: it doesn't specify the output format (e.g., list of integers), error handling (e.g., for q=0), computational limits, or whether the input rational must be in simplest form. For a tool with no annotation coverage, this is a significant gap.

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 brief and front-loaded with the core purpose in the first sentence. The domain/category tags are efficiently appended. However, the lack of essential details (like parameter meanings) means it's under-specified rather than optimally concise.

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 no annotations, no output schema, and 0% schema description coverage for a 2-parameter tool, the description is incomplete. It doesn't explain what the tool returns, how to interpret the continued fraction output, or handle edge cases. For a conversion tool with mathematical nuances, this is inadequate.

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?

Schema description coverage is 0%, so the schema only indicates p and q are required integers. The description adds no parameter semantics—it doesn't explain that p is the numerator and q is the denominator, or that q must be non-zero. With low schema coverage, the description fails to compensate, leaving parameters poorly documented.

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 verb ('Convert') and resource ('rational number to continued fraction'), making the purpose unambiguous. It distinguishes from sibling tools like 'cf_to_rational' by specifying the direction of conversion. However, it doesn't explicitly differentiate from 'continued_fraction_expansion' or other continued fraction tools, preventing 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 minimal guidance with the domain/category tags ('arithmetic', 'continued_fractions'), which imply context but don't specify when to use this tool versus alternatives like 'cf_to_rational' or 'continued_fraction_expansion'. No explicit when/when-not instructions or prerequisites are given.

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