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Presence API — Hands for AI Agents

test_action

Perform a defined physical action and report: open the door with the code, test the lock, run the appliance, stand where the robot will stand and measure. Returns video of the action, pass/fail against the written criteria, and measurements.

Input Schema

NameRequiredDescriptionDefault
actionYes
addressYes
deadlineNo
budget_capNo
pass_criteriaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose the return artifacts (video recording, pass/fail verdict against written criteria, measurements), which is genuinely useful since no output schema exists. It says nothing about prerequisites (site access, codes, whether a human or robot executes), what happens when the action fails or the deadline passes, or how budget_cap constrains the run — significant gaps for a real-world physical operation.

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: the verb front-loaded, examples inline, then the outputs. No filler; the example list is a bit dense but each clause adds distinguishing detail.

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?

A consequential real-world action tool with zero annotations, no output schema, and 0% parameter coverage needs far more: execution model, failure/timeout behavior, cost implications of budget_cap, and deadline semantics are all absent. The return-value sentence is the only thing preventing a 1.

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, so the description must compensate. It only hints at two of them — 'action' via examples and 'pass_criteria' as 'written criteria' — while 'address', 'deadline', and 'budget_cap' are never mentioned, leaving format and semantics (is address a street address, a unit, a coordinate?) undefined.

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?

States a specific verb ('perform a defined physical action') plus the reporting outcome (video, pass/fail against written criteria, measurements), and the examples (open door with code, test lock, run appliance, stand-and-measure) make the resource concrete. It never names or contrasts with a sibling, and 'stand where the robot will stand and measure' overlaps noticeably with stand_in, so an agent cannot fully rule out the alternatives from this text alone.

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

Usage Guidelines2/5

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

No explicit when-to-use or when-not-to-use statement and no mention of the sibling tools (stand_in, verify_location, environment_assessment, witness_event) that overlap in domain. Usage is only inferable from the example actions and the presence of pass_criteria.

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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