random_sample

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

With no annotations, the description carries the full burden. It explains the output (list of k unique items) and the without-replacement behavior. It does not mention error conditions like k > population size, but for a simple random sample this is acceptable.

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 concise with 5 lines, structured cleanly with Args and Returns sections, no unnecessary words.

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's simplicity and the presence of an output schema (though not shown), the description is largely complete. It covers purpose, parameters, and return value. A slight gap is not mentioning the error case when k > population size.

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 description adds meaning to both parameters beyond the bare schema: 'population: List of items to choose from' and 'k: Number of items to choose'. This compensates for the 0% schema coverage. However, it could be more explicit about constraints (e.g., k must be <= length of population).

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 the verb 'choose' and the resource 'k unique items from population without replacement', which is specific and distinguishes from the sibling 'random_choices' which likely does with replacement.

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 implies when to use (when without replacement) but does not explicitly state when not to use or compare to alternatives like 'random_choices' for with-replacement sampling.

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