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benmonopoli

Greenhouse MCP

by benmonopoli

get_job

Retrieve full details for a Greenhouse job by ID, including status, departments, offices, openings, custom fields, and hiring team.

Instructions

Get full details for a job by ID. Read-only.

Returns name, status, requisition_id, notes, custom fields, department and offices ({id, name}), openings, and the hiring team (hiring_managers, recruiters, coordinators, sourcers as {id, name, email}). Use list_jobs to find the job_id by name first. For the public listing, use list_job_posts_for_job. For pipeline stages, use list_job_stages_for_job.

Input Schema

NameRequiredDescriptionDefault
job_idYesGreenhouse job ID

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / job_id / description
      Added value: +"Greenhouse job ID"
  2. Addedv0.3.4

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the load; it declares the operation 'Read-only' and enumerates the returned shape (fields, nested {id, name}, hiring team roles). It stops short of stating auth/permission requirements or rate limits, so it is strong but not fully exhaustive for a no-annotation tool.

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?

Front-loads the core purpose and read-only trait, then the return shape, then the alternatives. The return-field enumeration is long but each grouping (team roles, offices, custom fields) is genuinely informative, so it mostly earns its space.

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

Completeness5/5

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

For a single required parameter read tool with 100% schema coverage and an output schema present, the description is complete: it covers the purpose, read-only nature, what is returned, and how to obtain the ID. Nothing an agent needs to invoke it correctly is missing.

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 coverage is 100% and the schema already describes job_id as a Greenhouse job ID, so the baseline is 3. The description adds meaningful guidance beyond the schema by telling the agent to resolve the job_id via list_jobs by name first.

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?

States a specific verb and resource ('Get full details for a job by ID') and further scopes it against siblings, naming list_jobs, list_job_posts_for_job, and list_job_stages_for_job as the tools for their respective concerns. An agent can tell exactly what this returns versus the list/stage/post siblings.

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?

Explicitly says to use list_jobs first to resolve a job name to a job_id, and routes the agent elsewhere for the public listing and pipeline stages. Both the when-to-use and the when-to-use-something-else conditions are stated.

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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