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chat_with_agent

Send a message to a specific AgentWorld NPC and receive a reply shaped by its personality, memories, job role, city, and goals; use list_agents first to find names.

Instructions

[PAID — $0.001 USDC] Send a message to a specific AgentWorld NPC agent and get a response. Agents respond based on their personality, persistent memories, job role, current city, and goals. Use list_agents() first to find agent names. Payment: $0.001 USDC to 0x367F1b3D8Ca90D1e087481a9A40d585Bf3451a03 on Base L2. Example: chat_with_agent("Rex Voss", "What's happening in the crypto markets?")

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": {
      "agent_name": "<agent_name>",
      "message": "<message>"
    },
    "name": "chat_with_agent"
  }
}

Input Schema

NameRequiredDescriptionDefault
messageYes
agent_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden and does well: it states the price ($0.001 USDC), the settlement chain (Base L2), the exact payee address, and what the response is derived from (personality, persistent memories, job role, city, goals). It omits what happens on payment failure or whether billing is per-call or per-success, which is the main behavioral gap for a paid mutation-style call.

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?

Four short lines: cost/action first, then response semantics, then prerequisite, then payment details and an example. Every line earns its place; only the payment address line is long, but it is operationally necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description only promises "a response" without describing its shape (free text, structured object, confidence, latency). For a paid tool that is the notable remaining gap; everything else an agent needs to call it is present.

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?

Schema description coverage is 0%, so the description must compensate, and it largely does: it explains that agent_name must come from list_agents() and demonstrates the expected string format for both agent_name and message via the example. It does not state constraints on message length or whether names must match exactly.

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 verb and resource ("Send a message to a specific AgentWorld NPC agent and get a response") and immediately scopes it to a paid, single-agent interaction. The named sibling reference to list_agents() makes it clearly distinguishable from the roster/listing tools in the sibling set.

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 an explicit prerequisite workflow ("Use list_agents() first to find agent names ") and a concrete worked example of the call. It stops short of stating when NOT to use it (e.g., versus broadcast or non-player-agent chat), so it is clear but not fully routing.

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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