Trace how a product grew

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

Beyond the sparse annotations, the description discloses important behavior: it takes 60-90 seconds, costs credits, rebuilds from multiple sources, and returns cached reports instead under certain conditions. This gives the agent a clear expectation of side effects, time, and cost. There is no contradiction with the 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 compact and front-loaded: the first sentence gives the trigger and primary action, the second conveys cost, caching, duration, and next step. No wasted words or redundant restating of the tool name.

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 paid, asynchronous operation with no output schema, the description covers all operational expectations: trigger, alternatives, duration, cost, caching, and polling mechanism. It is sufficiently complete for an agent to decide when to invoke and what happens next.

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%, giving baseline 3, but the description adds useful parameter semantics by linking the cache/freshness tradeoff to when refresh matters (costs credits vs. free cached result). It also clarifies that the primary input is a domain, even though the schema already names it.

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 what the tool does—reconstructs a product's growth story from 12 public sources—and explicitly distinguishes it from search_reports, which serves a different lookup purpose. It also points to get_trace for polling, reinforcing the tool's role within the workflow.

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 explicit when-to-use guidance: run when search_reports finds nothing or the user wants fresh data. It also explains cost and caching behavior (returning cached report free when fresh) and directs the user to poll with get_trace, defining the surrounding workflow.

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