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Presence API — Hands for AI Agents

stand_in

Be the human for an agent-run process: let the technician in, sign for the delivery, attend the walkthrough, answer the inspector's questions from a script; safety officer on site for a robot deployment (nurse). Returns video, the script as executed, and a written outcome.

Input Schema

NameRequiredDescriptionDefault
scriptYes
addressYes
budget_capNo
specialistNo
scheduled_atYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It does disclose the return payload (video, script as executed, written outcome), which is valuable given there is no output schema. However, for a costly real-world action that dispatches a person to an address, it says nothing about permissions, geographic constraints, cancellation, cost mechanics, or what happens if the human cannot complete the script.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense sentence with semicolon-separated use cases; nothing is truly wasted, but the list of vignettes crowds out the parameter and behavioral detail an agent actually needs before invoking it.

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

Completeness2/5

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

With no annotations, no output schema, and 0% parameter documentation, the description must do all the work. It covers the return shape but leaves three of five parameters undefined and omits any operational constraints for what is an irreversible, real-world dispatch.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 5 parameters. The description explains 'script' (questions answered from a script) and implies 'address' (on site), but budget_cap, specialist, and scheduled_at are entirely undocumented in both schema and description — the agent must guess at their meaning and format.

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 states a concrete verb and resource — dispatch a physical human to act on an agent's behalf — and grounds it with vivid examples (letting a technician in, signing for a delivery, attending a walkthrough). It's clear what the tool does, though it never explicitly contrasts with the nearest sibling, witness_event.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The examples imply when to use it (situations requiring a physical human presence), which is more than nothing. But there is no when-not guidance, no mention of prerequisites, and no differentiation from witness_event or verify_location, which an agent would need to choose correctly.

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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