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

Even with readOnlyHint=true and destructiveHint=false already present, the description adds substantial behavioral context: the disclosure-date anchoring and STOCK Act 45-day filing deadline, the aggregation logic (midpoint of disclosed ranges, distinct member counts), and the ranking semantics for direction. No contradictions with 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 moderately long but every sentence carries essential information: purpose, date anchoring rationale, aggregation detail, parameter behavior, and sibling differentiation. It is front-loaded with the primary use case and structured logically 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?

With no output schema, the description fully compensates by describing each row's contents (aggregated trades, distinct members, counts, estimated dollar flow, largest participants, latest dates). It also covers the key nuance of disclosure-date anchoring, making the tool's behavior and return shape clear enough for correct invocation.

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?

Although schema coverage is 100%, the description enriches parameter meaning by explaining the behavioral effect of each: direction ranks by estimated net buying/selling, chamber narrows to one chamber, and days references a trailing disclosure window anchored on filing dates. This adds value beyond the schema's terse field descriptions.

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 opens with a specific verb and resource ('Get the stocks members of Congress traded most over a trailing window, aggregated across EVERY member and ticker'), clearly distinguishing it from sibling tools. It explicitly contrasts with alternatives: 'without needing a ticker or a member name' and later names GetCongressionalTrades and GetMemberTrades for other granularities.

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?

Provides explicit when-to-use guidance ('what did Congress buy this week') and names exact alternatives for other scopes ('Use GetCongressionalTrades for one stock's underlying disclosures and GetMemberTrades for one member's'). This gives the agent clear decision criteria for selecting this tool over siblings.

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