linkedin_apply

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

With no annotations, the description carries full burden. It discloses persistent browser session, manual login first time, and returns confirmed flag, confidence, message, and screenshot path. It does not mention potential failure modes or rate limits, but covers key behavioral aspects.

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 three sentences, well-structured, and front-loaded with the main action. Every sentence adds value: purpose, session behavior, and return details. No wordiness.

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 explains the return value (confirmed flag, confidence, message, screenshot path) despite no output schema. Parameters are well-documented in schema. It could mention what happens if no jobs are found or fallback behavior, but overall it is sufficiently complete.

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 coverage is 100%, so the baseline is 3. The tool description adds no extra parameter information beyond what is already in the input schema. It mentions filters like 'remote' and 'dry_run' but does not provide additional semantic detail.

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 searches LinkedIn jobs and auto-applies using Easy Apply. It distinguishes itself from siblings like 'search_jobs' (search only) and 'indeed_apply' (different platform). The verb 'auto-apply' and resource 'LinkedIn jobs with Easy Apply' are 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 explains the first-run login process and reuse of the browser session, providing context on when to use. However, it does not explicitly state when not to use this tool versus alternatives like 'auto_apply' or 'search_jobs'. Still, the usage scenario is clear enough.

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