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benmonopoli

Greenhouse MCP

by benmonopoli

replace_hiring_team

Replace a job's hiring team by overwriting specified roles (sourcers, recruiters, coordinators, hiring managers); omitted roles remain unchanged.

Instructions

Replace the hiring team for a job. Write operation — overwrites existing members.

Only the roles you pass are replaced; omitted roles are left alone. Members missing from a passed list are removed and new ones are added. To find job_id: list_jobs → match by name. For member user_ids: list_users → match each person by name. Returns added, removed and any per-member errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesGreenhouse job ID
sourcersNoArray of {user_id: N} — replaces all sourcers
recruitersNoArray of {user_id: N, candidate_responsibility?: active|inactive|future|all} — replaces all recruiters
coordinatorsNoArray of {user_id: N, candidate_responsibility?: active|inactive|future|all} — replaces all coordinators
hiring_managersNoArray of {user_id: N} — replaces all hiring managers

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0
  2. Removedv0.3.3
  3. 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 carries the full burden and does so well: it flags this as a write operation, states that existing members are overwritten, that omitted roles are left alone, and that members missing from a passed list are removed. It stops short of covering permission requirements or irreversibility guarantees.

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?

Front-loaded with the action and its destructive nature, then the replacement semantics, then the lookup recipes, then the return shape. Every sentence earns its place with no filler.

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 five-parameter mutation tool with no annotations, the description covers the risky semantics (overwrite, per-role replacement, removals) and even hints at the return payload despite an output schema existing. Auth/permission prerequisites are the only notable gap.

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%, so the schema already documents each array and its {user_id} shape, giving a baseline of 3. The description adds real meaning on top: it explains that each passed list fully replaces that role and that absent lists are no-ops, plus how to source job_id and user_ids.

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 (replace) and resource (hiring team for a job), and the semantics of replacement distinguish it clearly from the sibling add_hiring_team_members, get_hiring_team and remove_hiring_team_member 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?

The description makes the selection condition clear implicitly: replacement is per-role and omitted roles are untouched, which is what separates it from the additive sibling. It also gives concrete discovery paths (list_jobs to find job_id, list_users to find user_ids), though it never explicitly names an alternative tool or a when-not-to-use case.

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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