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JRM-Global

getonbrd-mcp

by JRM-Global

Jobs by category

jobs_by_category

Retrieve open job vacancies filtered by a category. Use a valid category ID such as programming or machine-learning-ai to get paginated listings, optionally including full job descriptions.

Instructions

List open jobs in one category. Use list_categories for valid ids (e.g. "programming", "machine-learning-ai", "sysadmin-devops-qa").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNotrue = full job descriptions (functions, desirable, benefits); false = 400-char preview
pageNoPage number (1-based)
categoryYesCategory id, e.g. "programming"
per_pageNoResults per page (max 100)
Behavior3/5

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

No annotations were provided, so the description carries the burden. It clarifies 'open jobs' and the grouped by category behavior, but it doesn't mention pagination, full vs preview content, or whether it returns any global metadata. The schema partially covers these, so the description could add more context without contradicting anything.

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?

Condensed and front-loaded. The first sentence defines the core purpose, the second provides actionable parameter guidance with examples. Every word earns its place; no fluff.

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?

The schema covers parameter details and defaults, and the description adds the missing conceptual context (category ID source). Since this is a list operation without complex mutation or side effects, the description plus schema provide sufficient for correct invocation. Sibling tool names give extra orientation.

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 schema already describes all four parameters, so the baseline is 3. The description adds value by giving concrete example category IDs and explicitly mentioning that category must be a valid ID, making it easier for an agent to construct correct calls.

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 states a specific verb (List), resource (open jobs), and constraint (in one category). It also provides concrete category ID examples, distinguishing it from get_job (single job) and list_categories (category metadata).

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?

The description explicitly tells the agent to use list_categories to get valid IDs, which is a direct usage guidance for a prerequisite. It doesn't explicitly contrast with get_job, but the 'in one category' phrasing makes the scope clear 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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