Industry trading

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

The annotations already establish read-only, idempotent, open-world, and non-destructive behavior. The description adds meaningful scope beyond annotations: the ranking is based on the last trading day and can be ordered by value, volume, or trade count.

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 front-loaded with the core action and metrics, then gives a focused usage example and alternatives. It is short and every sentence contributes useful routing information.

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?

For a simple two-parameter read-only ranking tool, the description supplies the temporal scope, ranking dimensions, and sibling routing. It does not spell out the exact response shape, but the output is strongly implied and no output schema exists to rely on.

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%, so both parameters are already documented in the input schema. The description echoes the sort metrics but does not add syntax, defaults, or limit behavior beyond what the schema provides.

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 uses a specific verb and resource: "Rank the stock-market industries by trading on the last day." It also names the three ranking metrics, so the agent can distinguish this tool from siblings like fp_stocks and fp_indices.

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?

It gives a clear use case, "which industries had the most money flowing today," and routes follow-up detail requests to fp_stocks(industry=...) and fp_indices(query=...). It does not explicitly state when not to use the tool, but the context and alternatives are clear.

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