ASTRA MCP Server

sensor_fuse

Fuse audio, visual, and olfactory signals using cross-modal attention to integrate multimodal sensory data for downstream neuromorphic processing.

Instructions

Cross-Modal Attention Fusion

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "sensor_fuse"
  }
}

Input Schema

Name	Required	Description	Default
`includeAudio`	No
`includeVisual`	No
`includeOlfactory`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Sep 6, 2026

TDQS

D1.8/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. 'Cross-Modal Attention Fusion' offers only a conceptual hint and does not state whether the operation is read-only, mutates state, depends on prior sensor data, or returns a result. This is insufficient for an agent to anticipate side effects.

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 only three words and technically concise, but it is under-specified rather than efficiently informative. It reads as a title, not as a tool description, and every necessary behavioral or semantic detail is absent.

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?

With no annotations, no output schema, and no parameter explanation, the description leaves almost everything unspecified. An agent cannot tell what inputs to supply for a desired behavior, what the tool returns, or what effects it has on the system. The definition is not actionable.

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

Parameters1/5

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

Schema description coverage is 0%, and the description never mentions includeAudio, includeVisual, or includeOlfactory. It adds no meaning about how these booleans affect fusion, such as modality selection, weighting, or output shape. The description completely fails to compensate for the absence of parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Cross-Modal Attention Fusion' is a noun phrase rather than a clear verb-resource statement. It mostly restates the tool name and adds the vague qualifier 'attention,' leaving unclear what action the tool performs or what outcome it produces. It does not meaningfully distinguish sensor_fuse from sibling tools like sensor_process or sensor_visual.

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?

There is no guidance about when to use sensor_fuse versus alternatives such as sensor_process, sensor_visual, sensor_audio, or sensor_olfactory. No use case, prerequisites, or exclusions are described, so an agent cannot determine the appropriate invocation context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.