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Greenhouse

by io.github.pipeworx-io

Greenhouse Get Candidate

greenhouse_get_candidate
Read-onlyIdempotent

Get full candidate profile by ID. Returns resume, contact info, application history, interviews, and notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCandidate ID
_apiKeyYesGreenhouse Harvest API key

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoCandidate ID
emailNoPrimary email address
notesNoNotes on candidate
phoneNoPhone number
resumeNoResume text or URL
last_nameNoCandidate last name
first_nameNoCandidate first name
interviewsNoList of interviews
applicationsNoList of applications

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Full candidate profile with resume, contact info, and history",
+  "properties": {
+    "applications": {
+      "description": "List of applications",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "email": {
+      "description": "Primary email address",
+      "type": "string"
+    },
+    "first_name": {
+      "description": "Candidate first name",
+      "type": "string"
+    },
+    "id": {
+      "description": "Candidate ID",
+      "type": "number"
+    },
+    "interviews": {
+      "description": "List of interviews",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "last_name": {
+      "description": "Candidate last name",
+      "type": "string"
+    },
+    "notes": {
+      "description": "Notes on candidate",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "phone": {
+      "description": "Phone number",
+      "type": "string"
+    },
+    "resume": {
+      "description": "Resume text or URL",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-greenhouse-api-key",
+    "id": 12345
+  }
+]
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying the return content (resume, contact info, application history, interviews, notes), which is beyond what annotations provide.

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?

A single, well-structured sentence that front-loads the main action and lists key return components. No wasted words.

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?

Given the output schema exists and annotations cover safety and idempotency, the description is complete enough for this simple 2-parameter tool. It summarizes the main return fields adequately.

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% for both parameters (id and _apiKey). The description does not add additional meaning beyond what the schema already provides, so baseline score of 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 uses 'Get full candidate profile by ID' with a specific verb and resource, and lists returned data types. It distinguishes from siblings like greenhouse_list_candidates and greenhouse_get_job.

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 clearly implies when to use (to retrieve a specific candidate's full profile by ID), but does not explicitly mention when not to use or suggest alternatives like greenhouse_list_candidates for searching.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes with detailed descriptions, but some overlap exists between research tools like ask_pipeworx, deep_research, and bet_research, which could confuse an agent. The Greenhouse-specific tools are clearly separated by the 'greenhouse_' prefix, aiding disambiguation.

Naming Consistency3/5

Tool names follow snake_case but vary in style: some have a prefix like 'greenhouse_' or 'pipeworx_', others do not (e.g., ask_pipeworx vs. deep_research). The verb-object pattern is inconsistent (e.g., 'generate_llms_txt' vs. 'entity_profile'), making naming less predictable.

Tool Count2/5

35 tools is excessive for a single server, especially one named 'Greenhouse' which implies an ATS focus. The set aggregates multiple domains (ATS, data research, memory, prediction markets) without clear scoping, overwhelming the agent and reducing coherence.

Completeness3/5

The Pipeworx/data research subset is fairly complete with lookups, comparisons, verification, and subscriptions. However, the Greenhouse ATS subset lacks create/update/delete operations, leaving notable gaps. The mixed domains make overall completeness uneven.

Resources