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Robot Actions — Remote Device Control

get_visual_review

Get full detail for one AI Visual Review candidate (from list_visual_reviews), including the actual baseline, live, and diff images as images you can view directly. Use this to inspect a candidate and form your own verdict, then call resolve_visual_review with your decision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
review_idYesReview id from list_visual_reviews

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that it returns 'actual baseline, live, and diff images as images you can view directly', which is useful behavioral detail. It does not explicitly state read-only, but 'inspect' and 'view' imply no side effects. It doesn't mention other potential details like metadata, but for a detail-retrieval tool this is adequate.

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?

Two sentences with zero redundancy. The first sentence states the purpose and what is returned, the second gives usage guidance. Information is front-loaded and every phrase 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?

For a detail tool with no output schema, the description explains the key outputs (images) and the workflow (call resolve afterwards). It does not enumerate all possible fields (e.g., status, metadata), but 'full detail' implies more than images. Still, given the clarity of its role in the pipeline, it is reasonably 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?

Schema description coverage is 100% with the parameter review_id described as 'Review id from list_visual_reviews'. The description repeats this source, adding no new semantic value. Baseline 3 is appropriate since the schema already documents the parameter fully.

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?

Clear verb and resource: 'Get full detail for one AI Visual Review candidate'. It explicitly distinguishes from list_visual_reviews by specifying 'from list_visual_reviews' and from resolve_visual_review by noting the follow-up action. An agent can immediately identify its role in the workflow.

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

Usage Guidelines5/5

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

Explicitly states when to use it: 'Use this to inspect a candidate and form your own verdict, then call resolve_visual_review with your decision.' This directs the agent to the correct alternative (resolve_visual_review) and indicates this tool is for inspection before resolution.

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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