random_normal

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

With no annotations provided, the description carries the full burden of transparency. It accurately states the behavior (generating a normal random number), but does not disclose additional details like output type (float), constraints on stddev, or non-determinism. For a simple RNG, this level is acceptable, but it adds little beyond the name.

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 one efficient, front-loaded sentence with zero wasted words. It immediately states what the tool does, making it ideal for quick agent scanning.

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 simple nature of the tool, no output schema, and no annotations, the description adequately conveys the essence. It could be slightly more complete by mentioning that the output is a float or that the distribution is continuous, but the name and description together are sufficient for most use cases.

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 covers both parameters (mean and stddev) with clear descriptions and defaults, achieving 100% schema description coverage. The description itself adds no extra parameter detail, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Generate') and names the exact resource ('random number from a normal distribution'), clearly distinguishing it from sibling tools like random_integer or random_float. This leaves no ambiguity about the tool's core function.

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 usage context is implied by the description: use this tool when you need a random number from a normal distribution. However, it does not explicitly mention when not to use it or suggest alternative tools, leaving some room for interpretation among the many random_* siblings.

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