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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so safety is covered. The description adds genuinely useful behavioral context beyond that: it returns variable ids with names and a match score, which the annotations don't convey.

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 sentences, each earning its place: what it searches, worked examples of the mapping, and the return shape plus downstream usage. The core purpose is front-loaded.

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?

No output schema exists, but the description explicitly states the return contents (ids, names, match score), and the annotations carry the safety profile. Combined with 100% schema coverage, an agent has everything needed to call it and consume the result correctly.

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 the baseline is 3, but the description earns more by demonstrating query semantics with two natural-language-to-variable-id examples that show how free-text input is interpreted. Limit and _apiKey are left to the schema, which is fine since it documents them.

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 (Search) and resource (Google Data Commons statistical variables) scoped by plain-language indicator, with two concrete input->output mappings. It is clearly distinguishable from datacommons_observation, which it explicitly points to.

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?

Explicitly tells the agent what to do with the result: 'Use the id as `variable` in datacommons_observation', routing it to the correct downstream sibling. It does not state when NOT to use it (e.g. when a known id already exists), so it falls just short of full when/when-not coverage.

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