search_jobs

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions 'return structured results' without specifying the response format, pagination, authentication requirements, or any side effects. Since the tool is a read-only search, one might expect no destructive behavior, but that is not stated. The lack of detail on output structure and prerequisite conditions (e.g., login) is a notable gap.

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 well-structured with a clear 'Args:' list that is front-loaded after the purpose statement. Each parameter gets exactly one line with no unnecessary detail. It is efficient and easy to scan, making it highly usable for an agent.

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?

There is no output schema, so the description should explain what 'structured results' means, but it does not. It also does not mention whether authentication is required (siblings include login and check_session, suggesting a dependency). There is no guidance on pagination, sorting, or how results relate to downstream tools like get_job_details or easy_apply. For a tool that returns a collection, this is insufficient context for correct usage.

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 description coverage is 0%, so the description must fully document parameters. It does so effectively: each parameter is listed with an explanation, examples, or allowed values (e.g., date_posted: 'day', 'week', 'month'; job_type: full_time, etc.). It also clarifies the default for limit (10). However, it does not explicitly state that most parameters are optional filters (only keywords is required), though the schema implies this via defaults. This slight omission prevents a 5.

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 action ('Search LinkedIn jobs') and the resource ('jobs'), and specifies that it returns 'structured results'. It distinguishes itself from siblings like get_job_details (which fetches a specific job) and easy_apply (which applies to a job). The purpose is unambiguous and 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 implies this is the entry point for job discovery, but it does not explicitly state when to use it versus alternatives. It does not mention that get_job_details should be used after finding a job, nor does it exclude scenarios like 'use only when logged in'. The usage context is implied but not articulated.

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