list_data_domains

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

The description discloses a real behavioral trait beyond the annotations: the first call is a full fetch and takes several seconds, warning the agent about latency and a cold-cache penalty. Annotations already cover read-only/idempotent/non-open-world semantics, and the output schema covers return shape, so this performance note is the additive value.

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, front-loaded with the purpose and finish with the latency caveat; nothing is wasted or buried.

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 params, an output schema, and read-only annotations, the description only needs purpose, scope, and any call-shape caveats, all of which it delivers. It could be slightly more complete by pointing to get_data_domain as the drill-down step, but nothing required for a correct call 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a no-param tool applies. No schema semantics are repeated or contradicted.

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?

The description states a specific verb (List) and resource (LinkedIn data domains) and adds scope ('that have data for the user') plus what the result carries ('with row counts'). The plural/aggregate framing implicitly separates it from the singular sibling get_data_domain, though it never names that sibling explicitly.

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 line 'The first call fetches all data' hints that this is the discovery entry point and should be called before drilling into a domain, but it never explicitly says when to use this versus get_data_domain or what the follow-up is. Usage is implied rather than stated.

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