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xpayr_list_ai_agents

Retrieve a merchant's AI commerce agents with their status, assigned wallets, and spending policies to monitor autonomous payment operations.

Instructions

List all AI commerce agents managed by the merchant along with their status, assigned wallets, and spending policies.

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": "xpayr_list_ai_agents"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It does disclose the return contents (status, assigned wallets, spending policies) and the word "all" implies no filtering, but it says nothing about read-only semantics, pagination/result-size limits, or auth requirements for a merchant-scoped listing.

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?

A single front-loaded sentence with zero filler that names the verb, the resource, the ownership scope, and the returned data.

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 simple zero-parameter read tool with no output schema, the description covers what is listed and which fields come back, which is enough to call it correctly. The only missing piece is listing behavior at scale (pagination or caps), a minor gap given the tool's simplicity.

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 there is nothing for the description to disambiguate; baseline for a 0-param tool 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: "List all AI commerce agents managed by the merchant." The resource name and the merchants' agents scope make it clearly distinct from siblings like xpayr_list_agent_payment_intents or xpayr_create_ai_agent, though it never names them explicitly.

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: the agent can infer this is the enumeration call for agent records, and the returned fields (status, wallets, policies) hint at discovery use cases. There is no explicit when-to-use, no mention of when a different list tool applies, and no prerequisites or exclusions.

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