linkedin_apply_to_jobs_bulk

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

The description reveals multiple behavioral traits beyond the annotations: human-like pacing, skipping previously applied jobs, aborting on session/quota failure, reporting skipped jobs with specific unanswered questions, and the real-world consequence of submitting applications. The annotations only indicate readOnly=false and openWorld=true, so this description adds substantial safety and failure-mode context.

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 four sentences, each delivering actionable information: the batch apply action, pacing and skip behavior, failure handling and skipped-job reporting, and the approval requirement. No filler or repetition, front-loaded with the primary purpose.

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?

The description gives essential operational context for a complex mutation tool: it warns about real submissions, requires approval, and explains edge cases (already applied, session/quota aborts, unanswered questions). It does not describe the return value/output, but with no output schema and clear behavior, the missing return-type detail is not critical 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?

The schema covers most parameters (83% coverage), but the description adds interaction context: 'supply those answers and retry those jobs' clarifies the answers parameter, 'daily safety quota' explains maxApplications bound, and 'required question could not be answered' relates to stopOnUnknown. This goes beyond basic parameter descriptions.

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 begins with a specific verb and resource: 'Apply to several Easy Apply jobs in sequence'. It clearly distinguishes itself from the singular sibling linkedin_apply_to_job by emphasizing 'several' and 'batch'. The purpose is unambiguous and differentiates from sibling tools.

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 conveys when to use this tool (for several Easy Apply jobs) and includes an explicit prerequisite: 'get explicit user approval for the batch first'. It also mentions failure handling (aborts on session/quota failure) and skipped jobs due to unanswered questions, but does not explicitly state 'do not use for a single job' or name the alternative. However, the batch context and sibling list make the use case clear.

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