opinion_pool

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

With no annotations, the description carries full burden. It discloses that confidence is preserved, returns scores and winner, and enforces distribution constraints. However, it does not detail behavior for weighted ballots, tie-breaking, or seed parameter effects.

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 three sentences, front-loading the core purpose and key constraints. Every sentence adds essential information without redundancy.

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 complexity (3 parameters, nested types) and that it has an output schema, the description covers the main operation and ballot constraint but omits important context about seed, tie_break, and weight support, leaving some gaps for an agent.

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 coverage is 0% and the description only partially compensates by explaining the profile's ballot structure. Parameters like seed and tie_break are not described, leaving the agent to rely on the schema's $defs which are not explicitly tied to the tool's usage.

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 tool performs a linear opinion pool over probability-distribution ballots, specifies the output format (scores and winner), and distinguishes it from sibling tools by requiring distribution ballots only.

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 implicitly guides usage by emphasizing that ballots must be distribution ballots (summing to 1) and will error otherwise. This helps differentiate from sibling tools that handle other ballot types, but it does not explicitly state when not to use or mention alternative tools.

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