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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds substantial behavior beyond that: return shape, truncation behavior with truncated=true and total, the requirement to show targeting_notice to the user, German-language names, and workspace optionality when only one workspace exists. No annotation contradiction is present.

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 front-loaded with purpose and output, then organizes details by parameter. Despite covering many categories and behaviors, every section is relevant to correct invocation and there is no repeated or filler content.

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?

Although an output schema exists, the description still provides useful return and truncation context. It covers category selection, query behavior, limit semantics, workspace optionality, and the mandatory targeting notice, leaving no significant gap for correct invocation.

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?

With 0% schema description coverage, the description fully compensates by explaining all four parameters. It enumerates valid category values or facet names, explains query semantics per category, states limit max of 100, and explains workspace optionality.

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: finding LinkedIn targeting values. It also identifies the concrete output ({name, urn}) and names the downstream tools that consume it, so an agent can distinguish it from linkedin_estimate_audience and campaign management siblings.

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 usage context by saying the results feed linkedin_update_campaign_targeting, linkedin_create_campaign targeting, and linkedin_estimate_audience. It also explains category-specific query behavior, including when to omit query for fixed categories and when query is required for job titles, companies, locations, etc. It does not explicitly state exclusions or alternatives among similar search tools, so it falls short of a 5.

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