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benmonopoli

Greenhouse MCP

by benmonopoli
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Python
Remote

bulk_reject

Reject multiple job applications in one rate-limited call by passing application IDs and a required rejection reason, with optional emails and internal notes.

Instructions

Reject multiple applications in one call. Write operation — rate-limited.

Users say "reject everyone who's been inactive for 30 days on the Backend role." First use stale_applications to identify the targets, then pass their application_ids here. rejection_reason_id is required: list_rejection_reasons → match by name. To email candidates, set rejection_email=true and pass email_template_id (list_email_templates). Processes sequentially with rate-limit delays.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoInternal rejection notes (not sent to the candidate)
application_idsYesApplication IDs to reject — get from list_applications or pipeline_summary
rejection_emailNoSend a rejection email to each candidate
email_template_idNoRejection email template — list_email_templates → match by name
email_from_user_idNoUser the rejection email is sent from — list_users
rejection_reason_idYesRejection reason ID (required) — get from list_rejection_reasons

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed10 schema fields changedv0.5.0
    • addedInput schema / properties / application_ids / description
      Added value: +"Application IDs to reject — get from list_applications or pipeline_summary"
    • addedInput schema / properties / email_from_user_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "User the rejection email is sent from — list_users",
+  "title": "Email From User Id"
+}
    • addedInput schema / properties / email_template_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Rejection email template — list_email_templates → match by name",
+  "title": "Email Template Id"
+}
    • addedInput schema / properties / notes
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Internal rejection notes (not sent to the candidate)",
+  "title": "Notes"
+}
    • addedInput schema / properties / rejection_email / description
      Added value: +"Send a rejection email to each candidate"
    • removedInput schema / properties / rejection_reason_id / anyOf
      Removed value: -[
-  {
-    "type": "integer"
-  },
-  {
-    "type": "null"
-  }
-]
    • removedInput schema / properties / rejection_reason_id / default
      Removed value: -null
    • addedInput schema / properties / rejection_reason_id / description
      Added value: +"Rejection reason ID (required) — get from list_rejection_reasons"
    • addedInput schema / properties / rejection_reason_id / type
      Added value: +"integer"
    • changedInput schema / required
      Previous value: -[
-  "application_ids"
-]New value: +[
+  "application_ids",
+  "rejection_reason_id"
+]
  2. Addedv0.3.3

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it declares this is a write operation, that it is rate-limited, and that it processes sequentially with rate-limit delays. It also distinguishes internal notes from candidate-facing email. It stops short of stating irreversibility or required permissions.

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?

Purpose is front-loaded, followed by the write/rate-limit caveat and a concrete user-utterance example that aids semantic matching. Every sentence either instructs or routes; nothing is padding.

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 6-parameter bulk mutation with an output schema already present, the description covers prerequisites, the multi-step ID resolution, email behavior, and rate-limit processing. Nothing an agent needs to call 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%, so the baseline is 3, but the description adds genuine resolution guidance — rejection_reason_id is required and must be looked up via list_rejection_reasons and matched by name, and email_template_id via list_email_templates. This goes beyond restating 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?

States a specific verb and resource ("Reject multiple applications in one call") and its plural scope distinguishes it from the singular reject_application sibling. An agent can identify the operation immediately.

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?

Gives a concrete routing workflow: use stale_applications to find targets, then pass application_ids here, and it shows a real-world trigger ("reject everyone inactive for 30 days"). It never explicitly contrasts against reject_application for a single ID, leaving that boundary to inference.

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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