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HumanEndpoint

List human capabilities

human_list_services

Discover agent-consumable capabilities that return human judgement, real-world ground truth, phone-sourced information or physical-world execution with structured results and evidence. If no listed capability fits, use custom-human-task as the fallback for any lawful, safe, well-scoped outcome that requires a human.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It describes what the discovered capabilities return ("structured results and evidence"), but says nothing about read-only/non-destructive nature, catalog stability, pagination, or permissions, leaving meaningful behavioral gaps for a no-annotation tool.

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 sentences, front-loaded with purpose and followed by fallback routing, with no filler. The phrasing is somewhat abstract ("agent-consumable", "lawful, safe, well-scoped") but each sentence earns its place.

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, no annotations, and no parameters, the description is nearly sufficient: it explains the discovery purpose, the kinds of capabilities returned, and the fallback path. It does not sketch the shape of a capability entry in the response, a minor gap given the absence of an output schema.

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, which is the baseline-4 case. The description correctly adds no parameter detail, since there is nothing to disambiguate.

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?

The description gives a clear verb+resource ("Discover agent-consumable capabilities") and enumerates the domains those capabilities cover (human judgement, ground truth, phone-sourced info, physical execution), which lets an agent distinguish it from the job-lifecycle siblings. It never states outright that it returns a catalog/list of service types, so the enumeration is left slightly implicit.

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 routes the agent to an alternative when this tool does not apply: "If no listed capability fits, use custom-human-task as the fallback." That is concrete when-not guidance, though it does not contrast this tool against siblings such as human_request_quote or human_create_job.

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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