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 operation but does not explicitly mention that it is pure, has no side effects, or what the return value is. While obvious for addition, it falls short of full transparency.

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 a single, direct sentence with zero filler. It is front-loaded and every word earns its place, exemplifying appropriate conciseness.

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?

For a trivial addition tool with a clear input schema and an output schema (as indicated by the signal), the description is largely sufficient. It lacks explicit mention of edge cases or preconditions, but none are expected for this operation, making it nearly complete.

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%—the description does not mention parameters by name or add any nuance. The schema already declares a and b as required numbers, but the description adds no value beyond that, failing to compensate for the low 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 'Add two numbers together' uses a specific verb and resource, clearly stating exactly what the tool does. It is distinct from siblings like roll_dice and add_expense, so agents can easily differentiate.

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 gives no guidance on when to use this tool versus alternatives, nor any exclusions. There is no context about when addition is appropriate or not, leaving the agent to infer usage from the name and schema alone.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It correctly implies a random stochastic process and states the output ('return the results'), but does not explicitly mention randomness, the range of outcomes (1–6 per die), or that subsequent calls produce independent results. This is adequate for a simple tool but lacks any deeper 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 a single sentence, front-loaded with the core action, and contains no filler words. Every term contributes to understanding the tool's behavior.

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 low complexity (one parameter, simple output) and the presence of an output schema, the description is complete enough. It explains the parameter's role and the action's purpose. It could mention the non-deterministic nature more explicitly, but that is implicit for a dice-rolling tool, and the output schema likely covers return formatting.

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 zero description coverage for the parameter n_dice, so the description must compensate. It does so by framing n_dice as the number of dice to roll, adding semantic meaning to an otherwise bare integer field. However, it does not specify constraints like minimum value or positivity, which would have improved clarity further.

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 states a clear, specific action: 'Roll n_dice 6-sided dice and return the results.' The verb 'Roll' and resource 'dice' are unambiguous, and the tool is easily distinguished from siblings like add_numbers or list_expenses, which handle arithmetic or expense management.

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?

There is no guidance about when to use this tool versus alternatives, nor any exclusions or prerequisites. Sibling tools are unrelated, but the description provides no context for selection, leaving the agent to infer its suitability from the name alone.

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