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JRM-Global

getonbrd-mcp

by JRM-Global

Get job detail

get_job

Fetch a specific LATAM tech job by its ID or slug to retrieve its full vacancy details and metadata for candidate triage.

Instructions

Fetch one job by id (the slug in its URL). Requires GETONBRD_API_TOKEN — without it the API returns 401; prefer search_jobs, whose results already include descriptions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesJob id/slug, e.g. "ux-engineer-senior-admoai-santiago-4b10"
Behavior4/5

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

With no annotations, the description carries the disclosure burden. It clearly states the auth requirement and the 401 failure case, and implies the returned content may lack descriptions by recommending search_jobs for that. It could go further by explicitly stating whether descriptions are missing, but for a simple fetch-by-id tool this is reasonably transparent.

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?

The description fits useful guidance into one compact sentence, front-loading the core purpose before addressing authentication and the alternative. Every clause earns its place.

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 description explains what the tool does, how to authenticate, and which sibling to prefer. It is complete enough for a low-complexity one-parameter fetch, though there is no output schema and the description does not explicitly state the job content/detail fields returned.

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

Parameters5/5

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

The schema covers the parameter with an example, and the description adds critical extra meaning: the id is the slug from the job's URL. This teaches the agent what kind of value to pass, going beyond the raw schema.

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 states a specific verb and resource: 'Fetch one job by id (the slug in its URL).' It also distinguishes itself from the sibling search_jobs by noting that search_jobs already includes descriptions, which clarifies why an agent might choose one over the other.

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?

The description gives explicit usage context: use this tool to fetch a single job by its slug, and prefer search_jobs when descriptions are needed. It also warns about the required GETONBRD_API_TOKEN and the 401 result without it, giving the agent concrete conditions for invocation.

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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