Skip to main content
Glama
christophejlegros-lgtm

ASTRA — Unified Research Lab + MCP Server

sensor_fuse

Fuse audio, visual, and olfactory sensor data using cross-modal attention to create a unified perception stream for neuromorphic simulation.

Instructions

Cross-Modal Attention Fusion

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
includeAudioNo
includeVisualNo
includeOlfactoryNo
Behavior1/5

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

No annotations are present, so the description carries full burden. It does not disclose any behavioral traits such as whether the tool has side effects, is read-only, requires permissions, or what the output format is. This is a critical 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 extremely short (3 words) but this is under-specification rather than conciseness. It lacks essential information and does not 'earn its place' by providing value.

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?

Given the complexity of the tool (fusing multiple sensor modalities), the lack of annotations, no output schema, and 3 boolean parameters, the description is woefully incomplete. An agent cannot infer the tool's behavior, inputs, or outputs from this description.

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%, meaning no parameter descriptions exist in the schema. The description does not add any meaning beyond the parameter names (includeAudio, includeVisual, includeOlfactory). For a tool with 3 parameters, the description should explain how these booleans affect fusion behavior, but it does not.

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, not a clear verb+resource statement. It does not specify what the tool does (e.g., fuses sensor data, computes attention, etc.). Compared to sibling tools like sensor_audio or sensor_visual which are self-explanatory, this description is vague.

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 usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like sensor_audio, sensor_olfactory, or other fusion-related tools. An agent would have no basis for deciding to invoke this tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/christophejlegros-lgtm/ASTRA-Unified-ResearchLab-MCP-v2.8'

If you have feedback or need assistance with the MCP directory API, please join our Discord server