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by ai.sendraven
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list_conversion_goals

Read-only

List conversion goals: the event names counted as a conversion, each with its credit window in days. An emit_event call with one of these names is credited to the last email the person clicked inside that window; any other name is an ordinary event.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_conversion_goals"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover read-only and non-destructive status, and the description adds real domain behavior: each goal carries a credit-window in days and attribution lands on the last clicked email within that window, with all other events being ordinary. Return format granularity is described, though ordering or pagination is not mentioned.

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?

Two tight sentences: the first defines the output, the second supplies the attribution rule that makes the output meaningful. Nothing is redundant and the core definition leads.

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 zero-parameter read tool with no output schema, the description covers both what is returned (event names and credit windows) and the semantics of those values. Only minor operational details, such as ordering or whether an empty list is possible, are absent.

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 tool takes zero parameters, so the baseline is 4. There is no parameter content for the description to clarify, and none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List conversion goals') and immediately defines what is returned: event names plus the credit window in days. It does not reference the paired write sibling create_conversion_goal, so distinction is implied rather than explicit, keeping this at a 4.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the domain concept and how emit_event interacts with these goals, which implies when an agent would want to look them up. It never says when to call this versus create_conversion_goal or get_conversion_metrics, so usage must be inferred.

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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