Skip to main content
Glama

sensor_audio

Capture or simulate audio, then encode via A-JEPA from waveform to Mel spectrogram to latent representation for neuromorphic processing.

Instructions

A-JEPA Audio Encoding (Waveform → Mel → Latent)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesAudio parameters
Behavior2/5

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

No annotations exist, so description must disclose behavior. It only states an encoding pipeline, omitting critical traits such as whether audio is captured from mic or simulated, side effects, or output format. Behaviors like latency or permissions are absent.

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 terse (one sentence). While concise, it lacks necessary details, making it less valuable. Every sentence should earn its place, but this single sentence does not provide enough information to guide usage.

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 no output schema and a nested input with six parameters, the description is far from complete. It does not explain what the tool returns, processing details, or how to use the parameters effectively. The agent would be left with many unknowns.

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 100%, but only two parameters (simulate, frequency) have individual descriptions. The tool description adds no extra meaning; 'Waveform → Mel → Latent' does not explain sampleRate or durationMs. With gaps in schema descriptions, the description should compensate but fails.

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

Purpose3/5

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

Description mentions 'Audio Encoding' and the processing pipeline, indicating it encodes audio. However, it is vague on what exactly the tool does (capture? process? return encoded data?), and does not clearly distinguish it from sibling sensor tools like 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?

No usage guidelines provided. Description does not say when to use this tool versus alternatives like sensor_visual or sensor_olfactory, nor does it mention prerequisites or contexts for simulated vs real audio.

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-v2.7'

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