voice-agents
Design Production Voice Agents
Voice agent teams must balance latency, turn taking, speech quality, and control. This skill guides architecture choices and production design tradeoffs.
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Review the Skillstore skill "voice-agents" from https://skillstore.io/skills/sickn33-voice-agents.md and its manifest at https://skillstore.io/api/skills/sickn33-voice-agents/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
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Test it
Using "voice-agents". Need help choosing speech-to-speech or pipeline for a support agent.
Expected outcome:
Recommendation: use speech-to-speech when natural timing and emotional tone matter most. Use a pipeline when auditability, tool control, and debugging matter more.
Using "voice-agents". Review my turn taking design.
Expected outcome:
- Add semantic voice activity detection for starts and stops.
- Support barge-in so users can interrupt long answers.
- Define fallback behavior for noise, silence, and overlapping speech.
Using "voice-agents". Prepare a launch checklist for a voice agent.
Expected outcome:
Check latency budgets, response length, background noise handling, STT error recovery, barge-in behavior, and monitoring before release.
Security Audit
SafeThe only static finding is a false positive. SKILL.md line 68 uses Markdown backticks to list related skills, not Ruby or shell execution. No prompt injection or malicious intent was found in the reviewed file.
Risk Factors
⚙️ External commands (1)
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APA citation
sickn33. (2026). voice-agents security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-voice-agents/audits/5BibTeX citation
@techreport{sickn33-sickn33-voice-agents-2026,
author = {sickn33},
title = {voice-agents security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-voice-agents/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "voice-agents security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-07"
url: "https://skillstore.io/skills/sickn33-voice-agents/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-voice-agents:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Voice Agent Architecture Review
Compare speech-to-speech and pipeline designs before implementation.
Conversation Flow Planning
Plan turn taking, barge-in behavior, and short spoken responses for a new agent.
Production Readiness Checks
Review latency, noise handling, and STT error risks before launch.
Try These Prompts
Help me choose between speech-to-speech and a pipeline voice agent for [use case]. Compare latency, control, debugging, and user experience.
Design turn taking for a voice agent that handles [conversation type]. Include VAD, interruptions, silence thresholds, and fallback behavior.
Review this voice agent architecture for latency risk: [architecture summary]. Identify the slowest components and recommend budget targets.
Create a production readiness checklist for a voice agent serving [audience]. Cover barge-in, background noise, STT errors, response length, and monitoring.
Best Practices
- Start with a clear latency budget for every speech, reasoning, and synthesis step.
- Design spoken responses to be short, clear, and easy to interrupt.
- Test with noisy audio, overlapping speech, and real user pacing.
Avoid
- Treating voice as a text chatbot with speech attached.
- Using silence-only turn detection for complex conversations.
- Allowing long responses that block interruptions and increase latency.