get_recommended_jobs

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

No annotations are present, so the description carries the full burden of explaining behavior. It says the tool returns current recommendations, but it does not disclose read-only behavior, personalization basis, freshness, pagination, or failure modes. The 'get_' prefix implies read-only, but the description itself adds little beyond the output concept.

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, front-loaded sentence with no filler or redundant wording. It is appropriately concise for a simple retrieval tool, though it could have used its brevity budget to add a bit more behavioral or usage context.

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-only fetch with one optional parameter, the description gives the essential meaning. However, with no output schema and no annotations, it is missing useful context like the shape of results, pagination behavior, and how it differs from search_jobs, making the description adequate but not 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?

The only parameter, limit, is left entirely unexplained in the description. Schema description coverage is 0%, so the description should compensate, but it does not mention how the limit affects the number of recommendations or whether there is a maximum. The parameter is self-explanatory to some degree, but that is not enough to earn a higher score.

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 identifies the resource: jobs Naukri is recommending for the user, and the tool name reinforces a fetch/recommendation operation. It lacks an explicit verb like 'returns' or 'fetches' and does not contrast itself with sibling tools such as search_jobs, but the intended purpose is easily understood.

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?

No guidance is given for when to use this tool instead of alternatives like search_jobs, get_saved_jobs, or get_job_details. There is no mention of login/session requirements or any condition under which recommendations would be unavailable or inappropriate.

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