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PAL Commerce & Agent Revenue MCP

by io.github.enricoaboujaoude-droid
OverviewDiscussionsAdmin

Choose the best PAL AIEO catalog tool

recommend_catalog_offer

Free AIEO pricing/router tool. Give the number of products and whether you need remediation or audit; PAL returns the best paid AI-commerce catalog route and exact price before you spend anything.

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": {
      "product_count": "<product_count>",
      "goal": "<goal>"
    },
    "name": "recommend_catalog_offer"
  }
}

Input Schema

NameRequiredDescriptionDefault
goalYesUse remediation for prioritized corrective actions; audit for validation findings only.
product_countYesNumber of product records you need processed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / product_count / maximum
      Previous value: -500New value: +2000
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations, so the description carries the burden. It usefully discloses that the tool is free and returns pricing without committing spend, which signals a read/compute-only operation. It does not state permissions, rate limits, or confirm no write/side effects occur.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, front-loaded with the key selling point ('Free AIEO pricing/router tool') and then the mechanics. No filler, though 'AIEO' and 'AI-commerce catalog route' are jargon the agent must infer.

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 does describe the return ('best paid catalog route and exact price'), which is the critical piece an agent needs. Remaining gaps are minor: no mention of what happens at the 2000-product ceiling or whether results differ by goal.

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 goal enum is fully documented in the schema, so the schema does the heavy lifting. The description restates the inputs without adding format, range, or edge-case meaning beyond what is already structured.

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+resource: takes product count and goal, returns the recommended paid catalog route and exact price. It is distinguishable from sibling execution tools (catalog_audit, catalog_remediation) by its pricing/routing framing, though it never names a sibling explicitly to sharpen that contrast.

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?

Implies the usage context ('before you spend anything') and tells the agent what inputs to supply, but gives no explicit when-to-use vs. when-not, and no direction toward free_remediation_sample or recommend_agent_commerce_offer as alternatives for different needs.

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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