get_data_domain

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

The annotations already declare this as a read-only, idempotent, non-open-world operation, so the safety profile is covered. The description adds some context by saying it returns raw data rows from any LinkedIn domain, but it does not discuss pagination, data scope, or other behavioral limits beyond what the schema and annotations already provide.

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?

The description is a single front-loaded sentence with no filler. It communicates the core action and example resources efficiently.

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?

Given the simple three-parameter read-only operation, full schema coverage, output schema, and clear annotations, the description is largely complete. It could be improved by explicitly mentioning the dependency on list_data_domains, but that gap is minor and partially covered by the schema.

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%, so every parameter is already documented in the input schema, which sets the baseline at 3. The description reinforces valid domain examples like POSITIONS and SKILLS but does not add syntax or meaning beyond the schema for domain, limit, or offset.

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 and resource: retrieving raw data rows from a LinkedIn data domain, with concrete examples like POSITIONS and SKILLS. It does not explicitly differentiate this from the sibling list_data_domains, but the contrast between raw data rows and domain listing is reasonably clear.

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?

Usage is implied by the statement that this gets raw rows from any data domain, and the examples suggest valid domain values. However, it does not explicitly say when to use this versus list_data_domains or other sibling tools, nor does it state that the domain must first be discovered via list_data_domains.

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