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

No annotations are provided, so the description carries the full burden. It discloses the two possible response states ('status: running' or full report), advises to call again if not done, and explains that the research may still be running server-side. It could mention error handling or retry behavior, but is quite transparent for a simple polling tool.

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 efficient and front-loaded with the trigger condition. Every sentence earns its place: the trigger, the response behavior, the restriction against speculative calls, and an illustrative example. No filler or redundant 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 tool with one parameter and an output schema, the description covers all necessary context: when to invoke, what to pass, how to interpret the result, and what to do if still running. The output schema handles detailed return structure, so the description is sufficiently 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?

The schema only defines client_run_key as a string with 0% description coverage, so the description must compensate. It explains the key must come from a prior foresea_analyze_market call and provides an example usage, adding crucial context beyond the raw schema.

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 specifies the tool's purpose: to check the status of an asynchronous research run initiated by foresea_analyze_market after it timed out or errored. It also differentiates itself from siblings by focusing on polling/checking rather than initiating or analyzing.

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?

Explicitly states when to use (after foresea_analyze_market times out or errors with a client_run_key) and when not to use ('Do not call this speculatively'). It also instructs to only use keys from prior calls, leaving no ambiguity about the trigger context.

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