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OpenWeb-Ninja

OpenWeb Ninja MCP

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jsearch

Find job listings aggregated from Google for Jobs (LinkedIn, Indeed, Glassdoor) and access job details and estimated salaries.

Instructions

Job search aggregated from Google for Jobs (LinkedIn, Indeed, Glassdoor and more): search jobs, job details, and estimated salaries.

Operations (set "operation" to one of these; put its parameters in "args"):

  • search_v2 (required: query): Job Search V2

  • search (required: query): Job Search

  • job_details (required: job_id): Job Details

  • estimated_salary (required: job_title, location): Job Salary

  • company_job_salary (required: company, job_title): Company Job Salary

When to use: Use to find job postings. For salary data only use job_salary_data; for company reviews/ratings use realtime_glassdoor_data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoParameters for the chosen operation as key/value pairs (see the tool description for required params).
operationYesWhich endpoint to call. See the tool description for each operation and its parameters.
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the operations and required parameters but does not mention response format, pagination, rate limits, or limitations. The statement 'aggregated from Google for Jobs' adds some context, but depth is lacking.

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

Conciseness4/5

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

The description is well-structured: a summary sentence, a formatted list of operations with required params, and a clear usage note. It is concise without wasted words, though the operation list could be slightly more compact.

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

Completeness4/5

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

Given the multi-operation nature and lack of output schema, the description covers all operations, required parameters, and usage distinctions from siblings. It falls short only on optional parameters and response details, but is complete enough for invoking the tool correctly.

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?

Schema descriptions are generic placeholders, but the tool description adds meaning by mapping each operation to its required parameters (e.g., 'search_v2 (required: query)') and explaining that parameters go in 'args'. However, optional parameters are omitted.

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

Purpose5/5

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

Description clearly states it is a job search tool aggregated from Google for Jobs, listing specific operations (search, job details, salary). It distinguishes from siblings by naming alternative tools for salary and reviews.

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

Usage Guidelines5/5

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

Explicit 'When to use' section specifies using the tool for job postings, and directs to job_salary_data for salary-only and realtime_glassdoor_data for reviews, providing clear alternatives.

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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