mod_power

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

No annotations are provided, so the description carries full burden. It mentions efficiency for large numbers, which is a useful behavioral trait, but fails to disclose other critical aspects: whether it handles negative inputs, overflow/underflow behavior, error conditions (e.g., modulus zero), computational limits, or performance characteristics. For a computational tool with no annotations, this leaves significant gaps in understanding its behavior.

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 functionality, the second adds efficiency context, and the third provides domain/category tags. Every sentence adds value without redundancy, and there is no wasted verbiage. It effectively communicates the tool's essence in minimal space.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and parameters well but lacks details on behavior, error handling, and output format. For a computational tool, users need to know what to expect in terms of results and limitations, which are not addressed. It meets a basic threshold but has clear gaps.

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, so the description must compensate. It clearly defines all three parameters (base, exponent, modulus) by name and their role in the formula '(base^exponent) mod modulus', adding essential semantic meaning beyond the schema's type definitions. However, it does not specify constraints (e.g., modulus > 0) or input domains, leaving some ambiguity.

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 explicitly states the tool's purpose: 'Calculate modular exponentiation: (base^exponent) mod modulus.' It specifies the exact mathematical operation with all three parameters, clearly distinguishing it from siblings like 'power' (which lacks modulus) or 'modulo' (which lacks exponentiation). The domain/category tags further clarify its arithmetic nature.

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 implies usage for modular exponentiation with large numbers ('Efficient for large numbers'), but does not explicitly state when to use this tool versus alternatives. Among siblings, tools like 'power' (general exponentiation) and 'modulo' (remainder operation) exist, but no guidance is given on choosing between them. The context is clear but lacks explicit alternatives or exclusions.

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