ASTRA

sensor_olfactory

Read-onlyIdempotent

Simulate chemoreceptor responses to compound mixtures and concentrations, producing latent smell encodings for neuromorphic or AI olfaction tasks without hardware.

Instructions

Koniku Kore-inspired olfactory encoding (simulated chemoreceptors → latent; no hardware)

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_olfactory"
  }
}

Input Schema

Name	Required	Description	Default
`input`	Yes	Olfactory sensor 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 and openWorldHint=false, so the safety profile is covered. The description usefully clarifies that this is fully simulated with 'no hardware', which is context annotations cannot convey, but says nothing about determinism, latency, or output form.

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 sentence with the transformation front-loaded and the simulation caveat in parentheses. It earns its place, though the parenthetical trivia is arguably lower value than stating the return format.

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 read-only, no-output-schema tool, the description should indicate what the 'latent' output looks like (dimension, format). 'chemoreceptors → latent' gestures at it but is not enough for an agent to consume the result confidently.

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 reported at 100%, so the nested properties (compounds, concentrations, numReceptors, temporalPhase, neuronViability) are the schema's responsibility. The description adds no meaning about units, defaults, or how receptor count affects encoding, 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 transformation (olfactory encoding) on a specific resource, with 'chemoreceptors → latent' indicating input and output direction. The 'Koniku Kore-inspired' jargon and lack of an explicit sibling reference (sensor_visual, sensor_audio) keep it from a 5.

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 use this versus sensor_visual, sensor_audio, sensor_fuse, or sensor_process. The description only characterizes the mechanism, not the conditions that should route an agent here.

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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