open-greenhouse-mcp

get_activity_feed

Retrieve a candidate's activity timeline with notes, emails, and stage changes in chronological order. Understand a candidate's history at a glance.

Instructions

Get a candidate's activity timeline. Read-only.

Users say "show me Sarah's history" or "what's happened with this candidate?" To find candidate_id: search_candidates_by_name. Returns notes, emails, stage changes, and other timeline events in chronological order.

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": {
      "candidate_id": "<candidate_id>"
    },
    "name": "get_activity_feed"
  }
}

Input Schema

Name	Required	Description	Default
`candidate_id`	Yes	Greenhouse candidate ID

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.5.0Aug 1, 2026

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 full burden. It explicitly states 'Read-only' and describes the return content (notes, emails, stage changes) in chronological order, which are important behavioral traits. It does not cover every possible edge case (e.g., pagination), but for a simple read-only timeline it is sufficiently transparent.

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 concise and well-structured: a clear one-line purpose, a read-only declaration, example phrasing, a prerequisite link, and a summary of the return content. Every sentence contributes meaning without redundancy.

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 tool with one parameter and an output schema, the description covers purpose, behavior, usage context, and parameter acquisition. The output schema handles return values, so no further detail is needed. It is complete for an agent to select and invoke correctly.

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 provides 100% coverage for candidate_id with 'Greenhouse candidate ID'. The description adds value by pointing to search_candidates_by_name as a way to obtain the candidate_id, which is a useful cross-reference 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 clearly states the tool 'Get a candidate's activity timeline' with a specific verb and resource, and differentiates from siblings like get_candidate by focusing on timeline events (notes, emails, stage changes). It is specific and unambiguous.

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 provides clear usage context with example user phrases ('show me Sarah's history') and a prerequisite (use search_candidates_by_name to find candidate_id). However, it does not explicitly mention alternatives or when not to use this tool, so it misses the 'when-not' aspect.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.