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invidtiv
by invidtiv

Start a continuous vision stream for a device

android.vision.startStream

Initiates real-time screen streaming from Android devices to enable AI agents to visually monitor and interact with mobile interfaces using H.264 video decoding.

Instructions

Uses scrcpy standalone server raw H.264 stream + ffmpeg decoding. Creates/updates resource android://device//frame/latest.jpg.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serialYes
maxSizeNo
maxFpsNo
frameFpsNo
Behavior2/5

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

With no annotations, the description carries full burden but only mentions creation/updates of a resource. It omits critical behavioral traits: whether this is a long-running process, if it consumes significant resources, potential side effects on device performance, error handling, or how to monitor/stop the stream. The mention of 'continuous' hints at ongoing activity but lacks depth.

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?

The description is front-loaded with the core purpose and implementation details in two concise sentences. However, the second sentence could be more integrated, and it lacks structural elements like bullet points for clarity, but overall it's efficient with minimal waste.

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?

Given the complexity of starting a continuous stream, no annotations, no output schema, and 4 parameters with 0% schema coverage, the description is incomplete. It misses operational details (e.g., how to access the stream output, error conditions), making it inadequate for safe and effective use by an AI agent.

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%, so the description must compensate but adds no parameter details. It doesn't explain what 'serial', 'maxSize', 'maxFps', or 'frameFps' mean, their units, typical values, or how they affect the stream. This leaves all 4 parameters semantically unclear beyond schema constraints.

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?

The description clearly states the action ('start a continuous vision stream') and the resource ('for a device'), specifying it uses scrcpy server and ffmpeg decoding. It distinguishes from sibling tools like android.vision.snapshot (single capture) and android.vision.stopStream (termination).

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 description implies usage for continuous vision streaming versus snapshot alternatives, but lacks explicit when-to-use guidance, prerequisites (e.g., device connectivity), or comparisons with other vision or device tools. It mentions resource creation but not operational context.

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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