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kula-ai

@kula-ai/mcp-server

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by kula-ai

search_jobs

Search jobs by title with partial match support and filter by department, office, status, employment type, workplace, and more. Results are sorted by relevance.

Instructions

Search jobs by title (partial match supported) with optional filters. Preferred over list_jobs when you need to find jobs by name. Results are sorted by relevance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch jobs by title — partial match supported
department_idsNoComma-separated department IDs to filter by (includes descendants)
office_idsNoComma-separated office IDs to filter by
statusNoComma-separated statuses to filter by: draft, pending_approval, rejected, scheduled, published, closed, archived
employment_typesNoComma-separated employment types: full_time, part_time, contract, internship, temporary, seasonal, volunteer
workplaceNoComma-separated workplace types: office, remote, hybrid
confidentialNoFilter by confidentiality — true for confidential jobs only, false for non-confidential
job_post_listedNoFilter by job post visibility — true for publicly listed jobs only
primary_recruiter_idsNoComma-separated user IDs to filter by primary recruiter
primary_hiring_manager_idsNoComma-separated user IDs to filter by primary hiring manager
pageNoPage number (default: 1)
limitNoItems per page (default: 20, max: 100)
Behavior3/5

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

No annotations provided, so description must bear the burden. It mentions results sorted by relevance but lacks details on pagination behavior, read-only nature, or any side effects. Not contradictory, but minimal.

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?

Two concise sentences with no wasted words. Front-loads the core action and includes sibling differentiation.

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?

With 12 parameters and no output schema, the description covers the main query but omits output format, filter combination logic, and pagination details. Adequate but not complete.

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 coverage is 100%, so parameters are well-documented in the schema. The description does not add significant new meaning beyond 'optional filters' and 'partial match'. Baseline 3 is appropriate.

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?

The description clearly states the tool searches jobs by title with partial match and optional filters, distinguishing it from list_jobs by naming it explicitly as the preferred tool when finding by name.

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

Usage Guidelines4/5

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

Explicitly states preference over list_jobs for name-based search, providing clear guidance. Could add when not to use, but the sibling differentiation is strong enough.

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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