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

Annotations already mark the tool as read-only and non-destructive, and the description adds substantial behavioral context: it uses the connected LinkedIn account, shares the Classic provider-search budget with people discovery, and must respect quota_protection and retry_after_seconds. It also discloses the anti-abuse constraint about not bypassing people-search cooldowns. This goes well beyond the structured annotation fields.

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 compact: two sentences, with the core purpose front-loaded in the first sentence. The second sentence packs important quota and cooldown constraints without excessive wording. Minor jargon like 'Classic provider-search budget' could be clearer, but every sentence earns its place.

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 9 parameters and full schema coverage, the description provides the essential behavioral constraints needed to invoke the tool responsibly, including shared-budget and cooldown rules. It does not describe the return format or how results relate to get_job_posting_details, which would be useful since no output schema exists. Overall it is complete enough for safe and 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?

Schema description coverage is 100%, and each parameter already has a meaningful description in the schema. The description adds no parameter-specific detail beyond repeating categories like keywords, location, seniority, and job type. Baseline 3 is appropriate because the schema does the heavy lifting and the description does not need to compensate.

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 opens with a specific verb and resource: 'Search LinkedIn job postings by keywords, location, seniority, job type, and more.' This clearly distinguishes it from people-search siblings like search_linkedin_people by the object being searched. The filter list gives an agent immediate confidence about what this tool is for.

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 description implies when to use the tool by defining it as a job-posting search, and it provides a strong negative guideline ('must never be used to bypass a people-search cooldown'). However, it does not explicitly name alternatives or state when to choose this over search_linkedin_navigator or get_job_posting_details. Usage context is present but largely inferred from the tool's purpose.

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