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Greenhouse MCP

Greenhouse MCP

by benmonopoli
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

unreject_application

Reverse a rejection to return a candidate to active status in Greenhouse, restoring a previously rejected application to the hiring pipeline.

Instructions

Reverse a rejection, returning the candidate to active status. Write operation.

Users say "undo the rejection for Sarah" or "bring Sarah back." To get the application_id: search_candidates_by_name → get_candidate → find the rejected application in their applications array.

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": {
      "application_id": "<application_id>"
    },
    "name": "unreject_application"
  }
}

Input Schema

NameRequiredDescriptionDefault
application_idYesGreenhouse application ID of a rejected application

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / application_id / description
      Added value: +"Greenhouse application ID of a rejected application"
  2. Addedv0.3.4

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description must disclose behavior; it explicitly labels the operation as a 'Write operation,' which is critical for an agent to know. It also states the resulting state change ('returning the candidate to active status'), but doesn't address permissions, idempotency, or side effects beyond that.

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 is brief and front-loaded, with the purpose in the first sentence. The additional examples and workflow are purposeful and directly support usage, with no wasted words.

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?

For a single-parameter write operation with an output schema, the description covers the core purpose, the write nature, and the parameter acquisition workflow. It's sufficiently complete for an agent to understand and invoke, though it doesn't cover edge cases like calling on an active application.

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 application_id as a Greenhouse application ID, but the description enriches this by showing how to find it via search_candidates_by_name → get_candidate and how to map natural language to the parameter. This adds meaningful guidance beyond the 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 opens with 'Reverse a rejection, returning the candidate to active status,' which clearly states the action and its effect. It distinguishes from the sibling reject_application by being the inverse operation, and gives concrete user phrasings.

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 provides explicit examples of user intents ('undo the rejection for Sarah' or 'bring Sarah back') that trigger this tool. It also specifies a workflow to obtain the required application_id, setting clear context for when to call this tool, though it doesn't explicitly mention exclusions or alternatives.

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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