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Greenhouse MCP

Greenhouse MCP

by benmonopoli

list_job_permissions

Retrieve all job-level permissions for a specific Greenhouse user to audit access, identify role assignments, and confirm which jobs they can access. Read-only.

Instructions

List all job-level permissions for a user. Read-only.

To find user_id: list_users → match by name or email. Each row has its own id (needed for remove_job_permission), job_id, role_id (was user_role_id), role_name, and automated (true when created by a future-job rule). Site admins have no rows — they can access every job.

Input Schema

NameRequiredDescriptionDefault
user_idYesGreenhouse user ID — get from list_users

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / user_id / description
      Added value: +"Greenhouse user ID — get from list_users"
  2. Addedv0.3.4

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the operation is read-only, each row carries its own id, `automated` marks future-job-rule rows, and site admins return no rows because they implicitly access every job. It omits pagination and auth details, but the edge case and field semantics are strong for a list 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 purpose and read-only status, then prerequisite routing, then per-field meaning. Dense but each clause serves a function; the parenthetical field-by-field explanation is the only part that borders on verbose.

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?

An output schema exists, so return values needn't be enumerated, yet the description usefully explains row fields and the site-admin empty-result case. For a single-parameter read-only list tool this is close to complete, missing only pagination/volume expectations.

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% (baseline 3), and the description adds a small amount beyond the schema by explaining how to resolve the single parameter ('match by name or email' via list_users). The addition over the schema's own 'get from list_users' note is modest but real.

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 ('List all job-level permissions for a user') and immediately flags 'Read-only,' which cleanly separates it from the sibling mutations add_job_permission, remove_job_permission, and add_future_job_permission. An agent can identify the tool's scope without opening the schema.

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?

Provides prerequisite routing ('To find user_id: list_users → match by name or email') and points to a downstream consumer ('id' needed for remove_job_permission). It does not explicitly distinguish this from the closely related list_future_job_permissions sibling, so it falls short of a full when/when-not statement.

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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