linkedin_search_jobs

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

Annotations already declare this as a safe read-only, idempotent operation. The description adds meaningful behavioral context beyond those annotations: it states "Handles pagination automatically" and clarifies that the output is jobIds intended for subsequent tools. This gives the agent a clearer mental model of the tool's behavior, though it doesn't disclose edge cases or rate limits.

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 two efficient sentences: the first lays out the scope and filter list, the second explains pagination and the tool's role in the workflow. Every clause adds value, with no redundant phrasing or unnecessary detail.

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 complex search tool with 16 optional parameters and no output schema, the description covers the essential context: it's a read-only, paginated search that returns jobIds to be used with other tools. It doesn't elaborate on the full return structure, but the downstream tool linkage provides sufficient context for an agent to understand what to expect.

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 69% schema description coverage, the description compensates partially by listing many filters and offering practical advice (e.g., "Set true when planning automated applications" for easyApplyOnly, "best for high-competition roles" for datePosted, "Combine freely" for workplaceType). It does not, however, elaborate on the five parameters lacking schema descriptions (e.g., jobFunctionIds, fairChanceEmployer), so it doesn't fully close the gap.

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 clearly states the tool's function: "Search LinkedIn jobs using the full filter set" and lists many specific filters. It also differentiates this tool from siblings by designating it as "the entry point for every job workflow," distinguishing it from linkedin_get_job (fetch a single job) and linkedin_get_company_jobs (company-specific).

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 provides strong usage context by calling it "the entry point for every job workflow" and explaining that returned jobIds feed downstream tools. However, it does not explicitly mention when NOT to use this tool or point to an alternative like linkedin_get_company_jobs for company-scoped searches, so it stops short of full when/when-not guidance.

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