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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds real value beyond them: results are limited to the activated public dataset, and a not_ready state is explicitly distinguished from an unknown record — a behavioral nuance not inferable from any structured field.

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?

Two short sentences with zero filler, and the prerequisite lookup source is front-loaded before the caveats about dataset scope and result states.

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?

For a single-parameter read tool with full annotation coverage and no output schema, the definition covers preconditions, data scope, and the meaningful error/empty distinction. It stops short of characterizing the returned record's shape, which is a minor residual gap.

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 0%, so the description must carry the parameter burden. It does the essential part by specifying the ID's provenance (it comes from search_merchants), which is the key semantic an agent needs; it does not describe format or length constraints, but those are already in the schema.

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 and resource ('Read one ID') and ties it directly to the sibling that produces that ID ('returned by search_merchants'), so an agent can tell the lookup apart from the search without opening either schema. The scope 'activated public dataset' further narrows what record is returned.

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?

The phrase 'one ID returned by search_merchants' establishes the prerequisite flow: get an ID from search, then read it here. It does not mention the other siblings (get_data_coverage, get_methodology), so it lacks explicit exclusion guidance, but the intended usage context is unambiguous.

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