ASTRA

sensor_audio

Read-onlyIdempotent

Encodes audio waveforms into Mel spectrograms and latent vectors with an untrained MLP for ASTRA bio-hybrid simulation.

Instructions

A-JEPA-inspired audio encoding (untrained MLP; waveform → Mel → latent)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input": "<input>"
    },
    "name": "sensor_audio"
  }
}

Input Schema

Name	Required	Description	Default
`input`	Yes	Audio parameters

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.1.0Sep 23, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, covering the safety profile. The description adds a genuinely useful behavioral fact — the MLP is untrained, so emitted latents are not semantically meaningful — but says nothing about cost, determinism, or the shape/range of the output.

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?

A single compact parenthetical fragment with zero filler; the pipeline is front-loaded. It is efficient, though the terse telegraphic style asks the reader to decode it.

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

Completeness3/5

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

For a tool with a nested six-property object and no output schema, the description covers the what and the 'untrained' caveat but omits when to use it, typical input scenarios, and the nature of the returned latent. Annotations carry the safety profile, but usage context is missing.

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 nested input fields (source, channels, simulate, frequency, durationMs, sampleRate) are already documented in the schema. The description adds no format or range detail beyond that, so baseline 3 applies.

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?

States a specific resource and operation: audio encoding, with the transformation pipeline spelled out (waveform → Mel → latent). The 'untrained MLP' qualifier adds meaningful scope, and 'audio' distinguishes it from sensor_visual/sensor_olfactory siblings, though it doesn't explicitly compare itself to them.

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 on when to call this versus sensor_process, sensor_fuse, or the visual/olfactory sensor tools. It describes what the tool is but never states the conditions or context that should trigger its use.

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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