Can this skill fix audio latency issues in ElevenLabs?

Yes, it provides diagnostic scripts to measure latency and recommends specific configuration changes, such as switching to high-speed models like Flash 2.5 or optimizing buffer settings.

Which ElevenLabs models does this skill support?

The skill is optimized for all current ElevenLabs models including Eleven Flash v2.5, Eleven Turbo v2.5, and Eleven Multilingual v2.

Does it require specific access to Twilio logs?

The skill uses Bash, Grep, and Read tools to analyze local service logs and uses MCP tools to fetch live conversation data from ElevenLabs for a complete diagnostic view.

Can it help with agents interrupting users too frequently?

Yes, it evaluates turn-taking patterns in transcripts and suggests adjustments to 'interruptionSensitivity' and 'responseLatency' settings to balance natural flow.

How does it help with context injection failures?

It analyzes your application logs and agent initialization code to ensure lead data is correctly formatted as objects and properly passed to the agent's context window.

ElevenLabs & Twilio Agent Debugger

Name: ElevenLabs & Twilio Agent Debugger
Author: onesmartguy

byonesmartguy

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Analíticas y Monitorización

Troubleshoots and optimizes ElevenLabs conversational AI agents and Twilio call integrations through systematic diagnostic procedures.

Acerca de

A comprehensive debugging framework designed specifically for real-time voice AI integrations. This skill enables Claude to analyze failed calls, diagnose audio latency issues, and verify agent configurations within the ElevenLabs and Twilio ecosystem. It streamlines the troubleshooting process by interpreting error logs, reviewing transcripts for conversation breakdowns, and providing actionable remediation steps to improve agent performance, response speed, and overall reliability.

Características Principales

Deep analysis of ElevenLabs agent configurations, models, and voice settings
1 GitHub stars
Transcript evaluation to identify logic breakdowns and context injection failures
Audio quality and latency diagnostics for Twilio-integrated voice calls
Automated log interpretation for rapid root cause identification in voice services
Systematic 5-step debugging methodology (Observe, Reproduce, Isolate, Diagnose, Fix)

Casos de Uso

Debugging context injection where agents ignore provided lead or property data
Optimizing response latency and interruption sensitivity for natural conversations
Identifying why an AI agent fails to initialize or respond during a live call

Acerca de

Características Principales

Deep analysis of ElevenLabs agent configurations, models, and voice settings
1 GitHub stars
Transcript evaluation to identify logic breakdowns and context injection failures
Audio quality and latency diagnostics for Twilio-integrated voice calls
Automated log interpretation for rapid root cause identification in voice services
Systematic 5-step debugging methodology (Observe, Reproduce, Isolate, Diagnose, Fix)

Casos de Uso

Debugging context injection where agents ignore provided lead or property data
Optimizing response latency and interruption sensitivity for natural conversations
Identifying why an AI agent fails to initialize or respond during a live call