linkedin_get_saved_jobs

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

Annotations already declare the operation as read-only, idempotent, and non-destructive, so the safety profile is covered. However, the description adds no additional behavioral context such as pagination, ordering, or whether results are live or cached, leaving the tool's runtime behavior fairly opaque.

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 a single, direct sentence with no filler or redundancy. It is appropriately front-loaded with the main action and resource.

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 list operation with one optional parameter, a brief description is sufficient. The annotations and schema provide additional context, and no output schema is present, so the description need not elaborate on return values. The tool's scope is fully captured.

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 sole parameter 'limit' is fully described in the schema (default 50, min 1, max 200), so schema coverage is 100%. The description adds no extra parameter nuance, matching the baseline score for tools where the schema carries the semantic weight.

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 action ('List') and specific resource ('jobs the user has saved on LinkedIn'), distinguishing it from related tools like get_applied_jobs and search_jobs. It is specific and unambiguous.

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 implicitly conveys when to use this tool—to fetch the user's saved jobs—but it does not explicitly discuss alternatives or exclusions. Since the purpose is self-evident for this simple read operation, the usage guidance is adequate but not explicit.

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