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Greenhouse MCP

Greenhouse MCP

by benmonopoli
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

webhook_test_rule

Dry-run a webhook rule against the most recent matching event to preview results without executing actions. Verify rule behavior after creating or updating it.

Instructions

Dry-run a rule against the most recent matching event. Read-only.

Shows what would happen without actually executing the action. Use after webhook_create_rule or webhook_update_rule to verify behavior. To find rule_id: webhook_list_rules.

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": {
      "rule_id": "<rule_id>"
    },
    "name": "webhook_test_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
rule_idYesRule ID — from webhook_list_rules

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / rule_id / description
      Added value: +"Rule ID — from webhook_list_rules"
  2. Addedv0.3.4

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description must carry the behavioral burden, and it does disclose the key traits: it is a dry-run that 'shows what would happen without actually executing the action' and is 'Read-only.' It omits auth/permission requirements and rate-limit behavior, but covers the safety-critical disclosure well.

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-loads the purpose and read-only nature, then behavior, then usage and the rule_id pointer. Four short sentences, none redundant, nothing wasted.

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 simple 1-param read-only tool with an output schema (so return values need not be explained) and no annotations, the description supplies enough to invoke it correctly. Only minor gaps remain, such as what happens if no matching event exists.

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% and the single rule_id param is already documented as coming 'from webhook_list_rules.' The description repeats that pointer ('To find rule_id: webhook_list_rules') rather than adding new meaning, so baseline 3 applies.

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+resource ('Dry-run a rule') plus the scope ('against the most recent matching event'), and immediately marks it 'Read-only.' An agent can distinguish this from webhook_create/update/delete/list_rules 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?

Gives an explicit when-to-use ('after webhook_create_rule or webhook_update_rule to verify behavior') and routes the agent to webhook_list_rules for the required rule_id. It lacks an explicit when-not/exclusion, but the context is clear.

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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