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Greenhouse MCP

Greenhouse MCP

by benmonopoli
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_answer_option

Retrieve a demographic answer option by ID from Greenhouse ATS; read-only lookup. Get IDs from answer option lists.

Instructions

Get a demographic answer option by ID. Read-only.

To find IDs: list_answer_options or list_answer_options_for_question.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "answer_option_id": "<answer_option_id>"
    },
    "name": "get_answer_option"
  }
}

Input Schema

NameRequiredDescriptionDefault
answer_option_idYesAnswer option ID — get from list_answer_options

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / answer_option_id / description
      Added value: +"Answer option ID — get from list_answer_options"
  2. Addedv0.3.4

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden and does disclose the key trait ('Read-only'), which tells the agent this is a safe non-mutating call. However, it says nothing about what happens with an invalid or deleted ID (error vs. empty result) or any other behavioral edge case.

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 short sentences, zero waste, with the core purpose front-loaded and the ID-sourcing hint following immediately. Nothing extraneous.

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 tool is simple (one required param), an output schema exists so return values need no explanation, and the description covers purpose, safety posture, and ID acquisition. Only minor gap is the absence of failure-mode behavior for a bad ID.

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 description coverage is 100% and the schema already documents answer_option_id including the hint to get it from list_answer_options; the description only restates that sourcing hint. Per the baseline for full schema coverage, 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 states a specific verb and resource ('Get a demographic answer option by ID'), which is precise enough to distinguish it from sibling list_answer_options, list_answer_options_for_question, and get_answer without opening any 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?

It explicitly names the two sibling tools (list_answer_options, list_answer_options_for_question) as the way to obtain the required ID, giving a clear precondition for calling it. It stops short of stating when to prefer this single-fetch over those list tools or when not to use it.

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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