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machfive

by io.github.Bluecraft-AI
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List Campaigns

list_campaigns
Read-onlyIdempotent

List campaigns in the user's MachFive workspace.

CALL THIS FIRST before generate_sequence or generate_batch — you need a campaign ID to generate emails. If the user hasn't specified a campaign, call this and ask them to pick one.

Returns JSON array of campaigns with id, name, and created_at. Use the 'id' field as campaign_id in generate calls.

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_campaigns"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoSearch string to filter campaigns by name (case-insensitive substring match). Leave empty to list all.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / description
      Added value: +"Generic wrapper for non-object return types."
  2. Changed1 schema field changed
    • addedInput schema / properties / query / description
      Added value: +"Search string to filter campaigns by name (case-insensitive substring match). Leave empty to list all."
  3. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior, and the description adds useful context about the return format (array with id, name, created_at) and how to use the id as campaign_id. No contradictions with annotations.

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 three sentences with clear structure: what it does, when to use it, and what it returns. 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?

The tool is simple, and the description covers purpose, workflow, and output, complemented by a fully documented schema and a true output schema. The description is sufficient for an agent to select and invoke the tool correctly.

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?

The single parameter `query` is fully described in the input schema with a clear description (case-insensitive substring filter), so the description doesn't need to add more. It does reinforce that listing returns all campaigns when no filter is applied.

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 opens with a specific action ('List campaigns') and identifies the resource ('in the user's MachFive workspace'). It also distinguishes its role from the generate tools by explicitly stating it should be called first to obtain a campaign ID.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance: 'CALL THIS FIRST before generate_sequence or generate_batch' and instructs to ask the user to pick a campaign if none is specified. This gives clear direction against alternatives.

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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