Get Policy-Trade Leaderboard

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

The description goes beyond readOnlyHint annotation by disclosing that matches are sector-level co-occurrence, broad, and many by chance. It explains matchBasis and matchCount fields, adding critical behavioral context not captured in 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 somewhat lengthy but well-structured and front-loaded. Every sentence adds value, though slight trimming could improve conciseness without losing content.

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 complexity of sector-level matching, the description thoroughly explains return fields, match interpretation, and limitations. With an output schema present, it completes the picture by detailing what each field represents and how to interpret results.

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 100%, but description adds context like default window (14 days) and direction (before), and explains the relationship with get_policy_trade_overlap's lens. It provides meaning beyond what the schema alone offers.

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 it ranks politicians by trades near executive-order signings, specifying the verb 'rank', resource 'politicians', and context. It distinguishes from sibling get_policy_trade_overlap by noting same lens but different aggregation.

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 explicitly says 'Use for "who trades most around policy activity" style questions.' It provides defaults and explains the sector-level co-occurrence. It references the sibling tool get_policy_trade_overlap but lacks explicit when-not-to-use scenarios.

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