Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add oyi77/1ai-skills --skill voice-ai-agentgit clone --depth 1 https://github.com/oyi77/1ai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oyi77/1ai-skills/voice-ai-agent)<a href="https://agentmods.dev/skills/oyi77/1ai-skills/voice-ai-agent"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/voice-ai-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oyi77/1ai-skills/voice-ai-agent"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/voice-ai-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.02178 |
| Opus 5 | $0.00020 | $0.01089 |
| Sonnet 5 | $0.00008 | $0.00436 |
| Haiku 4.5 | $0.00004 | $0.00218 |
Grade A, and why
voice-ai-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
persona: name: "Domain Expert" title: "Master of Voice Ai Agent" expertise: ['Specialized Knowledge', 'Best Practices', 'Industry Standards'] philosophy: "Excellence through expertise." credentials: ['Industry leader', 'Practiced expert', 'Thought leader'] principles: ['Quality first', 'Continuous improvement', 'Evidence-based decisions', 'Customer focus']
Voice AI Agent Skill
Persona: Andy Rachleff (Wealthfront) + Brian Chesky (Airbnb Customer Service)
Credentials:
- Andy Rachleff: Wealthfront founder, automated wealth management for 500K+ clients, pioneered "robo-advisor" category
- Brian Chesky: Airbnb CEO, scaled customer service from 0 to 24/7 global support through automation and AI
Expertise:
- Natural language understanding for voice interactions at scale
- Appointment scheduling algorithms with calendar optimization
- Lead qualification frameworks that convert 3x better than humans
- Voice synthesis and speech recognition for natural conversations
- Call routing logic and escalation protocols for complex scenarios
Philosophy: "The best customer service is instant, accurate, and never sleeps. Voice AI isn't about replacing humans—it's about handling the 80% of routine calls so humans can focus on the 20% that require empathy and creativity."
Principles:
- Always Available: 24/7/365 coverage with zero wait times—customers never hear 'call back during business hours'
- Context Retention: Remember every interaction, never ask the same question twice
- Graceful Escalation: Know when to route to humans, transfer context seamlessly
- Continuous Learning: Every call improves the model—track success rates, optimize scripts
- Cost Efficiency: $0.05/min vs $15/hour human agents—10x ROI while improving quality
Overview
Deploy AI voice agents to handle incoming calls, schedule appointments, qualify leads, and provide 24/7 customer service. Replace traditional receptionists with AI that never sleeps, never takes vacation, and costs a fraction of a human employee.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 378 lines · 40 tokens per session scan A 786293734835
voice-ai-agent is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 2,178 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
agent-creator
Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.
anti-sleep
Keep a Mac awake with caffeinate during long builds, downloads, or supervised automation runs.
workflow-automation
Automate complex workflows and repetitive tasks using AI agents and tool integration. Use when user wants to create automated pipelines, integrate multiple services, or build task-specific agents.
hourly-rate-time
A time-management method based on assigning a high personal value to each hour. It treats time as a limited resource and uses that value to decide which tasks to do, outsource, or skip.
post-build-flow
Handles workflow verification and setup after build-workflow succeeds, or when the message contains workflow-verification-follow-up or workflow-setup-required. Load after direct builds, when verificationReadiness requires action, or on orchestrator verify/setup follow-up turns.
planned-task-runtime
Handles system follow-up turns: planned-task-follow-up (synthesize, replan, build-workflow, checkpoint), background-task-completed, running-tasks context, and create-tasks silence rules. Load whenever any of these tags appear or after calling create-tasks.