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DarkLvrd

agentic-linkedin

by DarkLvrd

Search jobs

get_jobs

Search LinkedIn jobs using keywords and a location ID to find relevant openings matching your criteria.

Instructions

Searches jobs by keywords and location id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsNo
locationIdNo
Behavior2/5

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 states the basic search behavior and does not mention return format, result limits, pagination, or whether empty criteria return all jobs. This is minimal coverage of the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no filler. The resource and all relevant parameters are mentioned front and center, making it highly concise while still communicating the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with only two optional string parameters, the description is close to adequate. However, with no output schema and no annotations, it leaves the agent guessing about return values and whether the parameters are required or mutually exclusive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does name both parameters and assigns them a role as search filters ('keywords and location id'), which adds meaning beyond bare string types. However, it omits details such as optionality, format of locationId, and how the filters combine.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Searches'), the resource ('jobs'), and the two search criteria ('keywords and location id'). It is not fully distinctive because it doesn't explicitly differentiate from sibling tools, but no sibling appears to offer job search, so the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when searching for jobs by keywords and/or location. It offers no explicit guidance about optionality, required parameters, or exclusions, but the intended use case is reasonably inferable from the text.

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

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