exponential_sample

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'random samples' but fails to describe key behaviors such as the output format (e.g., list of numbers), whether the seed parameter ensures reproducibility, or any performance considerations (e.g., large n values). This is inadequate for a tool with parameters and no annotations.

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, efficient sentence that directly states the tool's function. It avoids unnecessary words and is front-loaded with the core action. However, the domain/category tags are somewhat redundant and could be omitted for better focus.

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 has 3 parameters with 0% schema coverage, no annotations, and no output schema, the description is insufficient. It does not explain parameter meanings, output format, or behavioral traits, making it incomplete for effective use. The agent lacks critical information to invoke the tool correctly.

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%, meaning none of the parameters (n, rate, seed) are documented in the schema. The description does not compensate by explaining what these parameters mean (e.g., n is sample size, rate is the distribution's rate parameter, seed controls randomness). This leaves all parameters semantically undefined, which is a critical gap.

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 the tool 'Generate random samples from the exponential distribution', which provides a clear verb ('Generate') and resource ('random samples'), but it does not differentiate from sibling tools like 'exponential_cdf', 'exponential_pdf', or 'normal_sample'. The domain/category tags add context but do not enhance the core purpose statement.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks any mention of prerequisites, typical use cases, or comparisons to sibling tools (e.g., 'exponential_cdf' for cumulative probabilities or 'normal_sample' for normal distribution samples). This leaves the agent without direction on appropriate contexts.

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