prime_factors

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 tool returns 'the prime factorization as a list', which is useful behavioral information. However, it doesn't disclose important traits like input constraints (e.g., n must be positive, handling of large numbers, error behavior for non-integer inputs), performance characteristics, or whether duplicates are included for repeated prime factors. For a mathematical tool with no annotation coverage, this leaves significant gaps.

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 and front-loaded: the first sentence states the core purpose, the second adds return format, and the parenthetical provides domain context. Every sentence earns its place with zero waste, making it easy for an agent to parse quickly. The structure is logical and efficient.

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 low complexity (single integer input, list output) and no annotations or output schema, the description is minimally complete. It covers the basic operation and return type but lacks details on input constraints, error handling, and output formatting (e.g., sorted order, multiplicity representation). For a simple mathematical function, this is adequate but leaves room for improvement in guiding an agent fully.

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 a single parameter 'n' of type integer. The description adds no parameter-specific semantics beyond implying 'n' is the number to factorize. It doesn't clarify valid ranges (e.g., n > 0), special cases (n=0,1,negative), or formatting expectations. Since schema coverage is low, the description compensates minimally, meeting the baseline but not adding meaningful detail.

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 prime factors of a number' with the verb 'find' and resource 'prime factors', and specifies the return format 'as a list'. It distinguishes from siblings like 'is_prime' or 'prime_count' by focusing on factorization rather than primality testing or counting. However, it doesn't explicitly differentiate from potential factorization alternatives (though none are listed among siblings).

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 'Domain: arithmetic, Category: number_theory', which gives broad context but doesn't help an agent choose between this and siblings like 'divisors' or 'prime_gap'. There are no explicit when/when-not instructions or named alternatives, leaving usage decisions to inference.

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