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christophejlegros-lgtm

ASTRA Unified Research Lab MCP Server

sensor_visual

Encodes image or video inputs into V-JEPA 2 visual features for use in neuromorphic simulation pipelines. Handles custom sizes, channels, and simulated frames.

Instructions

V-JEPA 2 Visual Encoding (Image/Video)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesImage parameters
videoFramesNoNumber of frames (>1 = video)
Behavior1/5

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

With no annotations provided, the description must disclose behavioral traits. It only states the model name and modality, omitting any details about side effects, whether it captures from a camera, the role of the 'simulate' flag, return values, or whether it is a read-only operation. This is a significant transparency gap.

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

Conciseness2/5

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

The description is a single noun phrase, which is concise but severely under-specified. It lacks sentence structure and does not expand on what the tool does beyond the name. This is closer to a title than a description, reflecting under-specification rather than effective brevity.

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

Completeness1/5

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

The tool has two parameters with a nested object, no output schema, and no annotations. The description fails to explain the purpose of the encoding output, usage context, or relationship to other sensor tools. It is far from complete for an agent to invoke correctly without external knowledge.

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%, so the baseline is 3. The description adds the dimorphic 'Image/Video' context, but the schema already explains videoFrames with '>1 = video'. The description does not add meaningful semantics beyond the schema, so it stays at baseline.

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 'V-JEPA 2 Visual Encoding (Image/Video)' identifies the specific model (V-JEPA 2) and the modality (image/video), clearly distinguishing it from sibling sensors like sensor_audio and sensor_olfactory. While not a full verb phrase, it conveys the tool's function as an encoding operation for visual input.

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 guidance is provided on when to use this tool versus alternatives. Sibling tools include sensor_audio and sensor_olfactory, but the description does not mention any selection criteria, prerequisites, or contrast with other sensors.

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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