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BACH-AI-Tools

LinkedIn Data API MCP Server

search_jobs

Search LinkedIn jobs using keywords, location, company, salary, job type, experience level, and more. Filter by date posted, onsite/remote, and sort by relevance or recency.

Instructions

Search Jobs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYesExample value: golang
locationIdNoplease follow this link to find location id92000000
companyIdsNoplease follow this link to find company id
datePostedNoit could be one of these; anyTime, pastMonth, pastWeek, past24Hours
salaryNoit could be one of these; 40k+, 60k+, 80k+, 100k+, 120k+, 140k+, 160k+, 180k+, 200k+ Example: 80k+
jobTypeNoit could be one of these; fullTime, partTime, contract, internship Example: contract
experienceLevelNoit could be one of these; internship, associate, director, entryLevel, midSeniorLevel. executive example: executive
titleIdsNoplease follow this link to find title id by title
functionIdsNoplease follow this link to find function id
startNoit could be one of these; 0, 25, 50, 75, 100, etc. The maximum number of start is 975
industryIdsNoplease follow this link to find industry id
onsiteRemoteNoit could be one of these; onSite remote hybrid example: remote
sortNoit could be one of these; mostRelevant, mostRecent
Behavior2/5

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

No annotations are present, and the description does not disclose any behavioral traits such as read-only nature, rate limits, or side effects. The tool likely performs a search (assumed read-only), but this is not stated.

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

Conciseness1/5

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

The description is extremely brief (two words), but it lacks substance. Conciseness should not sacrifice information; this under-specification does not help the agent.

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

Completeness2/5

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

Given the complexity (13 parameters, many siblings, no output schema), the description is woefully incomplete. It does not explain return format, filtering behavior, or how this search differs from other search tools.

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 100%, so the input schema already documents all parameters thoroughly. The tool description adds no additional semantic value beyond what the schema provides, resulting in baseline 3.

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

Purpose2/5

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

The description 'Search Jobs' is a tautology that merely restates the tool name without specifying what kind of job search, scope, or differentiation from siblings like search_jobs_v2.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus similar alternatives (e.g., search_jobs_v2, get_company_jobs). The description lacks context for selection.

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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