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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses the pay-per-call model ($0.002 USDC via x402 on Base, Solana or Arc), that failed calls are not charged, and the hard data cutoff date. These are exactly the operational facts an agent needs before spending money on a call.

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?

Three tight sentences: what the data is, the staleness caveat, and the payment terms. Front-loaded with the resource identity and no filler.

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?

Trivial input surface (one optional param), an output schema already covers return values, and the description closes the remaining gaps: data currency limit and billing behavior. Nothing an agent needs to call it correctly is missing.

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 the single 'months' parameter (1-24, default 3) is fully documented in the schema. The description only adds the implied ordering ('latest months first') and does not restate the range or default, so baseline 3 applies.

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?

Names the exact resource (FAO Food Price Index monthly values, base 2002-2004=100) and enumerates the returned series (overall plus meat, dairy, cereals, oils, sugar). An agent knows precisely what dataset this returns and the ordering (latest months first). No sibling in the list covers food price indices, so differentiation is implicit but unambiguous.

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 clear usage context by warning that the published file ends in March 2018, which prevents an agent from misusing it as a current-price source. It does not, however, state an explicit alternative or a when-not-to-use rule beyond that staleness caveat.

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