Greenhouse MCP

convert_prospect

Convert a sourced prospect into an active candidate by applying them to a target job and setting the starting interview stage.

Instructions

Convert a sourced prospect into an active candidate on a job. Write operation.

Users say "move this prospect into the Backend pipeline." The prospect's application_id comes from their prospect record (get_candidate → applications array, where prospect is true). Target job_id from list_jobs → match by name.

Input Schema

TableJSON Schema

Name	Required	Description
`job_id`	Yes	Job ID to apply the prospect to — get from list_jobs
`application_id`	Yes	Prospect application ID to convert
`initial_stage_id`	No	Starting interview stage on that job (list_job_stages_for_job) — defaults to the first stage

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.5.0Oct 5, 2026

addedInput schema / properties / application_id / description
```
Added value: +"Prospect application ID to convert"
```

addedInput schema / properties / initial_stage_id

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Starting interview stage on that job (list_job_stages_for_job) — defaults to the first stage",
+  "title": "Initial Stage Id"
+}

addedInput schema / properties / job_id / description

Added value: +"Job ID to apply the prospect to — get from list_jobs"

Addedv0.3.4Apr 15, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose 'Write operation' and that the prospect becomes an active candidate on a target job, but says nothing about permissions required, reversibility, whether the prospect record is removed, or side effects such as notifications. Useful but incomplete for an unannotated mutation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and write-nature are front-loaded in the first two short sentences, and the remaining sentences give input-sourcing workflow. The 'Users say...' sentence is slightly filler but does map natural language intent to the tool, so it earns most of its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be explained, but for an unannotated write tool the description omits key operational context: side effects of conversion, error cases, and prerequisite state (e.g., prospect must exist and not already be converted). Adequate rather than complete.

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 coverage is 100%, so the baseline is 3, and the schema already says job_id comes 'from list_jobs'. The description adds real meaning by specifying that application_id is the prospect's application (identified via get_candidate where prospect is true), but it leaves initial_stage_id entirely to 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 ('Convert a sourced prospect into an active candidate on a job'), which is distinguishable from siblings like create_candidate, create_application, and advance_application. An agent can tell what this does and that it is a state transition, not a creation.

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 gives practical routing context — the user phrasing to expect ('move this prospect into the Backend pipeline'), plus where the two required IDs come from (get_candidate → applications array with prospect=true; list_jobs → match by name). It does not state when NOT to use this versus the many application/candidate siblings, so it stops short of full when/when-not guidance.

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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