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AAJ Marketing Engines

List marketing engines

list_engines
Read-onlyIdempotent

Lists every AAJ marketing engine: its id, the question it answers, and its category. Engines cover unit economics, pipeline forecast, budget allocation, retention, A/B significance, SEO/GEO scoring, ad spend and pricing.

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_engines"
  }
}

Input Schema

NameRequiredDescriptionDefault
categoryNoOptional filter. Words are matched against the engine's category, id and skill title (for example "pricing", "retention" or "seo audit"), then against its summary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / category / description
      Previous value: -"Optional filter, matched loosely against the engine's category."New value: +"Optional filter. Words are matched against the engine's category, id and skill title (for example \"pricing\", \"retention\" or \"seo audit\"), then against its summary."
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description adds value beyond that by disclosing the shape of each returned entry (id, question, category) and the breadth of engine topics, which matters because there is no output schema.

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 sentences, zero filler, with the core purpose and returned fields front-loaded ahead of the topical coverage list. Every clause carries information.

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?

With no output schema, the description usefully compensates by naming the fields each engine entry carries and the categories covered. It omits pagination, result counts, and whether engines can be unavailable/disabled, but it is otherwise sufficient for a zero-required-parameter read tool whose annotations cover safety.

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 optional 'category' parameter is thoroughly documented there, including the matching behavior and fallback to summary. The description adds nothing about the parameter, so the baseline of 3 applies.

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 ('Lists every AAJ marketing engine') and enumerates the fields returned (id, question, category) plus the domain coverage. It implicitly distinguishes itself from run_engine/describe_engine by being the enumeration endpoint, but never names a sibling explicitly, so it falls short of a 5.

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?

Usage is only implied: an agent can infer this is the discovery call to make before describe_engine or run_engine, but the description never says when to use it, when not to, or what alternative exists. No prerequisites or sequencing guidance is given.

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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