Skip to main content
Glama
alphaparkinc

Personal Agent Ambient Noise Auditory Focus Masker Skill

Personal Agent Ambient Noise Auditory Focus Masker Skill

OpenClaw Ecosystem Dual-Org Sync Zero Dependencies Model Context Protocol Production Grade

Zero-dependency acoustical Speech Intelligibility Index (SII) distraction auditor, cognitive throughput degradation modeler, and colored noise masking soundscape synthesizer.

Architecture

flowchart TD
    Soundscape[Ambient dBA, Speech %, Fluctuation dB] --> SIIAuditor[Speech Intelligibility & Distraction Engine]
    SIIAuditor --> DistractionScore[Distraction Index & Working Memory Loss]
    TaskDomain[Deep Coding vs Linguistic Writing] --> MaskingSynthesizer[Colored Noise Masking Synthesizer]
    MaskingSynthesizer --> NoiseProfile[Pink/Brown Noise Target dBA & Spectral Slope]

Related MCP server: personal-agent-skills

Quickstart

from client import PersonalAgentAmbientNoiseAuditoryFocusMasker

agent = PersonalAgentAmbientNoiseAuditoryFocusMasker()
res = agent.evaluate_acoustic_distraction_risk(ambient_dba=62.0, speech_presence_pct=40.0)
print(f"Distraction: {res['distraction_risk_score']} | Memory Penalty: {res['working_memory_throughput_penalty']}")

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    B
    maintenance
    Enables deterministic room acoustics analysis through MCP tools that compute axial, tangential, and oblique standing wave modes, Bonello and Bolt criteria compliance, Schroeder cutoff frequency, and Sabine/Norris-Eyring RT60 decay across octave bands for rectangular rooms. Also derives optimal speaker and sweet-spot coordinates with SBIR notch predictions and calculates the acoustic treatment area needed to hit target reverb times for podcast, mixing, home theater, or listening use.
    4
    8 npm
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables quantifying vocal fold collision doses and dysphonia risk from speaking duration, sound level, pitch, hydration, and cumulative vocal load, then prescribing SOVT-based vocal rest and recovery protocols.
    7
    MIT