linkedin_get_applied_jobs

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, covering the safety profile. The description adds valuable behavioral context by explaining that the data source is authoritative (LinkedIn's own record) versus server-local, which affects interpretation of the results. No contradictions with annotations.

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 sentences with no filler. It front-loads the core action and immediately provides a meaningful differentiator. Every clause 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?

For a simple read tool with one optional parameter and strong annotations, the description is complete. It clearly states what is returned (jobs the user applied to), identifies the authoritative source, and names an alternative. The lack of an output schema is mitigated by the clear purpose and read-only semantics.

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% with a single parameter 'limit' documented with its default value. The description adds no additional parameter details, so the baseline score of 3 is appropriate given that the schema already explains the parameter fully.

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 uses the specific verb 'Read' and clearly identifies the resource: LinkedIn's own record of jobs the user has applied to. It also explicitly contrasts with linkedin_get_application_history, distinguishing it from a closely related sibling tool.

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 directly states when to use this tool: to get the authoritative, complete record from LinkedIn, and contrasts it with linkedin_get_application_history for applications made through the server. This provides clear when-to-use and when-not-to-use guidance.

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