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

With no annotations, the description carries the full burden and does so: it discloses the $0.99 USDC price, the x402 PaymentRequired result on unpaid calls, and that payment is verified and settled before execution. It also pre-empts surprises by listing refused request classes.

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 purpose is front-loaded in the first sentence, with payment and refusal details following in a logical order. The long enumeration of return fields is dense but each item is decision-relevant; a little trimming of that list would tighten it further.

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?

There is no output schema, so the description must describe returns itself, and it enumerates the executive answer, cited URLs, claim/evidence matrix, conflicts, confidence, risks, and next actions in both JSON and Markdown. Combined with the payment flow disclosure, an agent has everything needed to invoke and interpret this tool.

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 description coverage is 100% and each parameter is documented in the schema (including depth and time_window defaults), so the schema does the heavy lifting. The description only restates the parameter list ('research question plus an optional company, domain, time window, and depth') without adding syntax or semantics beyond 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 names a specific verb and artifact ('Create a cited research decision memo from public sources') and enumerates the output contents, so the agent knows exactly what it gets. However, it never differentiates itself from the sibling company_intelligence_report, which plausibly overlaps on company-scoped research, leaving the agent to infer the boundary.

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 states the applicable domains ('For business, technical, and general public research') and gives explicit exclusions (private-person dossiers, fabricated citations, restricted scraping, trading signals, automated medical/legal/financial/employment/insurance decisions). This is strong when/when-not guidance, though it never names an alternative tool for the refused cases.

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