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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description still adds real behavioral context: what the payload contains (units, year, data-quality flag) and the critical caveat that identifiers are numeric domain-specific codes, not names.

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?

Purpose and authority are front-loaded in the first two sentences, followed by the code caveat and a compact example. The middle sentence is list-dense, but every clause identifies a supported query class rather than padding.

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 carries the return-value burden and does so (numbers with units, year, quality flag). It also documents the domain-code dependency and gives an end-to-end example, so an agent has everything needed for a 6-parameter 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 100%, so 3 is the floor. The description goes further by stressing that area/element/item are numeric domain-specific codes rather than names, and provides a fully worked example mapping codes (QCL/231/5510/15) to meanings, which reduces mis-invocation risk.

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 resource ('Observations from a FAOSTAT domain — the actual numbers') and what they carry (units, year, data-quality flag), then names the exact question classes it is authoritative for. It is clearly distinguished from faostat_dimensions and faostat_domains, which supply codes rather than numbers.

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 context for when to use it ('how much <crop> did <country> produce in <year>', trade flows, fertiliser/pesticide, emissions, food balance) and a prerequisite routing rule: pass codes obtained from faostat_dimensions. It stops short of stating when not to use it or naming a competing sibling tool to avoid.

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