get_sector_flows

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

No annotations are provided, making the description the sole source for behavioral disclosure. It appropriately identifies the data as research-only, returns institutional positions, and cautions against inferring intent. However, it does not mention whether the tool is a simple read operation or has any side effects, rate limits, or pagination behavior. With no annotations, the description provides adequate transparency but could be more comprehensive.

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 well-structured with a brief introduction, argument descriptions in a list, and a return format example. It is concise and front-loaded with the critical warning about data limitations. The only improvements would be to remove the redundant 'Research data only' phrase if the same information is already in the tool title (but title is null), so it earns its place.

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 (2 parameters, no output schema), the description covers the purpose, the data nature, and the return format with an example. It is largely complete for a straightforward query tool. However, it does not explain what 'risk_posture' means in the output, which would be helpful. Sibling tools are not explicitly differentiated, but the purpose is distinct enough.

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?

The description adds meaning beyond the input schema by explaining that 'quarter' is a quarter code and 'sector' is an optional GICS sector filter with an example. Schema coverage is 50% (only sector has a description), but the description compensates by providing context for both parameters. It does not list valid quarter codes or explain the format, which would be helpful, but the combination of schema and description is sufficient.

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 returns per-sector institutional capital flow intelligence for a quarter, specifying the data is research-only and should not be used to infer manager intent. The verb 'get' combined with 'sector flows' makes the tool's purpose unambiguous and distinguishes it from sibling tools like 'get_manager_holdings' which focus on individual managers.

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 warns about data limitations ('do not infer manager intent or future direction') and indicates this is for research purposes. It mentions an optional GICS sector filter, but does not explicitly contrast with sibling tools or specify when to use alternatives like 'get_consensus_portfolio'. The usage context is clear but lacks exclusions.

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