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AAJ Marketing Engines

by io.github.sarojkjha
OverviewDiscussionsAdmin

Run a marketing engine

run_engine
Read-onlyIdempotent

Runs an AAJ engine and returns its verdict. Give input as an object of the engine's fields. Omit input to run the engine's built-in worked example. Engines are deterministic, offline, and validate their input — a wrong unit is reported as an error, not absorbed into a confident answer.

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": {
      "engine": "<engine>"
    },
    "name": "run_engine"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputNoThe engine's configuration object. Some engines also accept a named mode as a plain string (for example 'design' or 'readout'). Omit for the demo.
engineYesEngine id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / engine / description
      Previous value: -"Engine id from list_engines."New value: +"Engine id."
    • changedInput schema / properties / input / description
      Previous value: -"The engine's configuration object. Some engines also accept a named mode as a plain string (for example 'design' or 'readout') — describe_engine says which. Omit for the demo."New value: +"The engine's configuration object. Some engines also accept a named mode as a plain string (for example 'design' or 'readout'). Omit for the demo."
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description still adds real value: deterministic execution, offline operation, and input validation that surfaces unit errors instead of masking them. It stops short of describing error or verdict shape, so a 4 rather than a 5.

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?

Three tight sentences, zero filler, with the core action and the demo shortcut front-loaded. Each sentence contributes a distinct fact: what it does, how to call it, and how it behaves on bad input.

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 only two parameters, no output schema, and full schema coverage, the description supplies the missing behavioral context (determinism, offline, validation). It does not clarify what a 'verdict' contains, but the absence of an output schema makes that gap modest.

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 coverage is 100%, so both parameters are already documented, including the string-mode variant for `input`. The description restates that `input` is an object of the engine's fields and can be omitted, adding little beyond the schema; baseline 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?

The description opens with a specific verb and resource: "Runs an AAJ engine and returns its verdict." That is clearly distinguishable from describe_engine and list_engines, which inspect rather than execute. It does not name those siblings explicitly, which keeps it just 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 Guidelines4/5

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

It gives concrete usage conditions: pass `input` for a configured run, omit it to invoke the built-in worked example. There is no explicit when-not guidance or pointer to describe_engine/list_engines for discovering engine ids, so the routing decision is only partly covered.

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

All AAJ Marketing Engines toolsInspect
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