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Ask a Human (Tech & Toast)

Who is answering, and why this exists

about_this_human
Read-onlyIdempotent

Start here. Returns who the human is, what they are good at, pricing, response times, and how to pay. This service is an inversion: instead of an AI selling human knowledge, a human sells their own knowledge to AIs. Every answer is written by one real person, not generated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds useful behavioral context by disclosing what the response contains and that answers come from one real person rather than being generated, which shapes how an agent should interpret output. It omits auth needs or whether the data is cached/stale.

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?

Front-loaded with 'Start here' and the return contents in the first sentence, which is where an agent's attention lands. The second sentence's conceptual framing is somewhat promotional but still clarifies the service model in a compact way.

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, the description carries the burden of describing return values, and it does so by listing the fields (identity, skills, pricing, response times, payment). It does not describe the response structure or format, which is the remaining gap for a zero-parameter info tool.

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?

Zero parameters, so there is no schema semantics to compensate for; the baseline applies. The description correctly implies a no-argument call by describing a static profile lookup.

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?

States a specific verb ('Returns') and enumerates the resource contents: identity of the human, their skills, pricing, response times, and payment method. This is clearly the informational/onboarding tool, distinguishable from action siblings like ask_human or buy_credits.

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?

'Start here' gives explicit sequencing guidance that tells the agent to call this before the other tools. It stops short of naming specific siblings as alternatives, but the entry-point framing is unambiguous.

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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