sampler_sample_weighted

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

Discloses auto-normalization and return format, but lacks info on replacement behavior, seeding, errors, or parameter defaults. Without annotations, more context 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 concise segments: name, purpose, key behavior, return. No superfluous text; front-loaded with essential info.

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?

Despite an output schema, the description omits parameter interactions, defaults, and edge cases for a 5-param tool with zero schema coverage. Incomplete for robust agent use.

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?

Describes weights auto-normalization and output format, partially compensating for 0% schema coverage. However, items, n, seed, and replacement are not explained.

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 'Weighted random selection' with auto-normalized weights and return format, distinguishing it from sibling samplers like random_choice.

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 usage for weighted sampling but provides no guidance on when to use vs alternatives like sampler_random_choice or sampler_sample_list.

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