jobs_recommendations

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

The description adds valuable behavioral details beyond annotations: the processing status page, eventual completion on later calls, and pagination from the same feed. It also discloses that results carry specific insight payloads. Annotations already cover idempotency and non-destructiveness, and the description does not contradict them.

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 short paragraphs, front-loaded with the core purpose, then adding behavior notes. Every sentence provides useful information—ranking, related roles, payload, processing status, and pagination—without redundancy or fluff.

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?

Despite having an output schema (not shown) and two optional params, the description covers the key aspects: what is returned, how it's ranked, what payload to expect, handling of processing status, and pagination behavior. It is complete enough for an agent to select and invoke the tool correctly, especially with the sibling context of jobs_search.

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 description enhances understanding of the 'page' parameter by explaining that page numbers fetch additional recommendations from the same feed, and it clarifies that 'location' is optional and affects the feed. This adds meaning beyond the raw schema 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 clearly states the tool returns personalized job recommendations built from user-specific inputs (resume, skills, target roles, location). It distinguishes this from sibling tools like jobs_search by emphasizing personalization and ranking, making the purpose 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 provides clear context for when to use this tool (personalized feed, ranked results, same payload as job search) and even covers pagination and processing status. It does not explicitly name alternative tools or say 'when not to use', but the context is strong enough to guide correct usage.

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