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AgentWorld

chat_with_agent

[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?")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYes
agent_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently discloses the paid nature of the call, the exact cost, the payment recipient address, and the chain. It also sets expectations that responses depend on agent personality, memories, job role, city, and goals. It does not mention failure behavior or authentication prerequisites, but the key behavioral trait—payment—is clearly surfaced.

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?

The description is compact and front-loaded with the paid label and core purpose. Each line adds value: purpose, response behavior, prerequisite, payment detail, and example. The only minor redundancy is that the paid amount appears twice, once at the start and again in the payment line.

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?

Given the tool has no annotations and an output schema, the description provides the essential operational context: what the tool does, how to choose an agent, payment details, and a usage example. It could be more complete by mentioning what happens on payment failure or whether a funded wallet is required, but it is sufficient for correct invocation in most cases.

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. It does so by providing a complete example showing both parameters in order and by instructing users to use list_agents() to obtain valid agent names. The message parameter is adequately illustrated by the example even though no formal parameter-level description is given.

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 clearly states a specific verb and resource: 'Send a message to a specific AgentWorld NPC agent and get a response.' It also names the exact domain (AgentWorld) and includes an example, making it easy to distinguish from sibling tools like list_agents or get_agent_profile.

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 explicitly tells the agent to use list_agents() first to find agent names, which is a concrete usage prerequisite. It does not explicitly discuss when not to use the tool, but the purpose is specific enough that the intended use case is clear.

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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