analysis.holders

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

Without annotations, the description carries the full burden. It discloses the output fields (wallet address, position size, side) and implies read-only behavior with 'View'. It could be more explicit about side effects, but it's sufficient.

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?

Two sentences with no fluff. The first sentence states the purpose and key parameter, the second adds the use case. Every sentence is informative.

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?

No output schema is present, so the description compensates by describing the return fields. It also provides context about 'smart money sentiment'. However, it lacks details on error conditions or condition_id format, but for a simple retrieval tool it is fairly complete.

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 100%, so baseline is 3. The description adds value by explaining the output fields (wallet, size, side) beyond the schema, which only describes the parameters. This helps the agent understand what data will be returned.

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 action ('View') and the resource ('largest position holders in a Polymarket market by condition_id'), distinguishing it from sibling tools like analysis.arbitrage or analysis.compare.

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 provides a usage context ('useful for gauging smart money sentiment on a market'), implying when to use it. However, it does not explicitly mention when not to use it or reference alternatives.

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