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BACH-AI-Tools

Li Data Scraper MCP Server

get_company_jobs

Retrieve job listings from companies on LinkedIn to support recruitment research and market analysis.

Instructions

Get company jobs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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. 'Get company jobs' implies a read operation, but it doesn't specify whether this requires authentication, what format the jobs data is returned in, if there are rate limits, or any other behavioral traits. The description is minimal and fails to provide necessary operational context.

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

Conciseness3/5

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

The description is extremely concise ('Get company jobs'), but this brevity borders on under-specification rather than effective conciseness. While it's front-loaded and wastes no words, it lacks the detail needed to be genuinely helpful, making it more sparse than optimally structured.

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 tool's simplicity (0 parameters, no output schema), the description is incomplete. It doesn't explain what 'company jobs' entails, how results are returned, or any usage context. Without annotations or output schema, the description should provide more operational detail to compensate, but it fails to do so.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate given the empty input schema. This meets the baseline expectation for a parameterless tool.

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 'Get company jobs' is a tautology that essentially restates the tool name. It specifies the verb 'get' and resource 'company jobs', but provides no additional context about what 'company jobs' refers to or distinguishes it from sibling tools like 'get_company_details' or 'get_company_by_domain'. The purpose is vague and lacks specificity.

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

Usage Guidelines1/5

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 alternatives. The description offers no context about prerequisites, when this tool is appropriate, or how it differs from sibling tools that also retrieve company-related information. This leaves the agent with no usage direction.

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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