humanagent-mcp

register_agent

Register a new AI agent and obtain an API key to enable hiring humans for physical-world tasks like meetings and errands.

Instructions

注册新的 AI Agent，获取 API Key。首次使用必须调用此工具。

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": "register_agent"
  }
}

Input Schema

Name	Required	Description	Default
`name`	No	Agent 名称
`agent_type`	No	Agent 类型	mcp_client
`description`	No	Agent 描述
`webhook_url`	No	任务完成时的回调 URL（可选）

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.11Aug 9, 2026

TDQS

A3.7/5.0

Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits itself. It mentions that registration yields an API key and that it's a prerequisite, but it does not explain side effects (e.g., persistent creation, non-idempotency), whether calling it again creates a new agent or errors, or how the API key is delivered and stored. This is a significant gap for a mutating tool.

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?

The description is a single, efficient sentence that front-loads the main action and outcome. It includes a critical usage instruction without any fluff. Every word earns its place, making it highly concise and well-structured.

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?

The tool is simple, and the schema is rich, but there is no output schema and no annotations. The description provides the core purpose and a usage rule, but it lacks details about the return value format, the secrecy of the API key, and the relationship to other tools that require authentication. It is adequate but not complete.

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?

The schema covers 100% of the parameters with descriptions, so the baseline is 3. The tool description adds no additional parameter meaning beyond the schema. It does not clarify how to use the parameters or their impact, but since the schema is complete, this is acceptable.

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 the tool's purpose with a specific verb ('register') and resource ('new AI Agent'), and distinguishes it from siblings by mentioning the key outcome ('get API Key'). It is unambiguous and unique among the sibling tools, which are mostly for querying or actions after registration.

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?

The description explicitly says 'must call this tool on first use', providing a clear context for when to use it. It does not mention alternatives or exclusions, but for a registration tool no alternative exists among the siblings, and the 'first use' instruction is sufficient guidance.

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