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

Rich disclosure beyond annotations: CC0 public-domain data, 404-with-no-charge on no match, price and free tier, failed calls free, and an explicit explanation of why readOnlyHint=false ('not marked read-only because each call is charged'). This proactively reconciles the non-obvious annotation.

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?

Front-loads the returned-fields list, then usage, example, and pricing in a logical order with no filler sentences. It is long but nearly every clause carries actionable information; only the pricing/payment detail is somewhat dense.

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?

With no output schema, the description compensates by enumerating the returned fields, and it covers error behavior, cost, and licensing. An agent has everything needed to invoke and interpret the call.

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 already 100%, so baseline is 3; the description adds value by clarifying the name-or-id choice and supplying concrete example values (name=Spotify, id=Q689141) that show the expected formats in practice.

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?

States a specific verb+resource ('Facts about a company') and enumerates the concrete fields returned (website, founding date, HQ, industries, CEO, tickers, LEI). An agent can immediately distinguish this from siblings like wikipedia, domain, or token_report without opening the schema.

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?

Gives explicit when-to-use ('enrich leads, vendors and counterparties or ground an answer about a company') and an implied scope limit ('best for established and listed companies'), plus a worked example. It does not name a specific alternative sibling to use instead for small/private entities, so it falls short of the 5 bar.

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