math_random_number_generator

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

No annotations provided, so description must fully disclose behavior. It reveals implementation (crypto.getRandomValues) and security stance, but omits error behavior, parameter constraints, statefulness, or side effects. With zero annotations, more detail is needed.

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?

Three sentences with key information front-loaded. The 'Menu ID' phrase is slightly redundant but not detrimental. No fluff; each sentence adds value.

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?

With 5 required params and no output schema or annotations, the description is insufficient for an agent to understand how to generate specific random values. It relies on a separate describe_tool call, indicating intentional incompleteness.

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 has 5 required parameters with 0% coverage. Description lists output types but does not map them to the 'operation' parameter or explain min/max/count/inclusive roles. It fails to add meaning beyond the schema.

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 it's a cryptographically secure random number generator listing output types (integers, floats, booleans, UUIDs, hex, base64). However, it does not differentiate from sibling 'data_random_data_generator', and the name 'math_random_number_generator' could be confused with a pure math tool.

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 CSPRNG and not Math.random, implying usage for security-critical random generation, but does not explicitly state when to use vs alternatives or provide exclusion criteria. Directs to describe_tool for more guidance.

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