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

Without annotations, the description carries full weight for transparency. It discloses the rejection-sampling technique, absence of modulo bias, anonymity, rate limiting, and transparency via echoed DRBG bytes. This is highly informative for an agent.

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 two concise sentences, front-loaded with the core purpose. Every clause adds value without redundancy. Highly 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 no output schema, the description should clarify the return value. It mentions 'echoing DRBG bytes' but does not specify the primary output (e.g., a list of dice roll results). This gap reduces completeness for an 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?

Schema description coverage is 0%, so the description must add meaning to the parameters. It does not explicitly describe 'count' or 'sides', though the context of dice rolls makes them intuitive. The description fails to provide essential parameter documentation.

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 that the tool performs 'dice rolls' using rejection sampling to avoid modulo bias, distinguishing it from sibling tools like 'random' and 'random_bytes' which serve general random generation. The purpose is explicit and specific.

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 mentions 'anonymous and rate-limited' which informs about usage context, but does not explicitly provide when-to-use or when-not-to-use guidance relative to sibling tools. However, the purpose is so specific that appropriate usage is implied.

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