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Voice Agent Design

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mohitagw15856
voice-agent-design

Design a voice AI agent for phone or in-app conversations — call flows, interruption handling, escalation to humans, and the metrics that catch a bad voice experience. Use when asked to design a voice agent, automate a phone line, spec an IVR replacement, or review why callers hate an existing voice bot. Produces a voice agent spec: persona and disclosure policy, conversation architecture, barge-in and repair behaviour, human-handoff rules, and a launch scorecard.

Overview

Publishermohitagw15856
Repositorypm-claude-skills
Skill namevoice-agent-design
Stars
1.4K
Forks
257
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mohitagw15856 on GitHub. Read the source before you install it.

Installation

Install the Voice Agent Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/mohitagw15856/pm-claude-skills/tree/main/plugins/pm-agentnative/skills/voice-agent-design
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git /tmp/pm-claude-skills
mkdir -p .claude/skills
cp -r /tmp/pm-claude-skills/plugins/pm-agentnative/skills/voice-agent-design .claude/skills/voice-agent-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Voice Agent Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Voice Agent Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Voice Agent Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Voice Agent Design Skill

Voice is the least forgiving agent surface: no screen to fall back on, dead air reads as failure within two seconds, and the caller is often already annoyed. This skill designs voice agents around the medium's real constraints — turn-taking, interruption, repair — instead of shipping a chatbot with a text-to-speech voice.

What This Skill Produces

  • A scope decision: which call intents the agent owns end-to-end, which it triages, which go straight to humans
  • A conversation architecture: openings, turn design, confirmation strategy, repair loops
  • Barge-in, silence, and error behaviour — the mechanics that decide whether it feels alive or infuriating
  • Human-handoff rules with context transfer, and a launch scorecard

Required Inputs

Ask for (if not already provided):

  • The line and its traffic: what people call about (top intents with rough volumes), current handle times
  • What the agent may actually do — which systems it can read/write, what it can promise
  • The escalation reality: human hours, queue lengths, what happens after-hours
  • Compliance context: recording consent, disclosure requirements, regulated statements in this domain

Design Method

  1. Scope by intent, ruthlessly. From the intent list, the agent owns only intents that are (a) high-volume, (b) completable with its actual system access, and (c) low-stakes-if-wrong. It triages everything it can identify but not complete. It immediately passes anything emotional, legal, or high-value — a furious caller is a human's job on the first turn, not after three failed bot turns.
  2. Disclose and set the frame in the first five seconds. The agent says it's an AI (increasingly required by law; always required by trust), what it can do, and how to reach a human ("say 'agent' anytime"). Hiding the escape hatch inflates containment metrics and rage in equal measure.
  3. Design turns for ears, not eyes. One question per turn · ≤2 sentences before yielding · numbers and options in threes at most ("I can do A, B, or C — which one?") · never read a paragraph. Anything long ("your options are…") gets offered as SMS/email instead of spoken.
  4. Engineer the mechanics that make it feel alive:
    • Barge-in on: the caller can interrupt any utterance; the agent stops mid-sentence and processes.
    • Latency masked: acknowledge within ~1s ("let me check that…") whenever a lookup exceeds it; dead air past 2s is where trust dies.
    • Confirmation proportional to stakes: implicit for low stakes ("okay, Tuesday…"), explicit read-back for money, addresses, and anything irreversible.
    • Repair, not repeat: on a misunderstanding, change strategy — rephrase, offer options, or fall to keypad — never re-ask the same question the same way twice.
  5. Make the handoff a feature. Triggers: caller asks (always, instantly) · two failed repairs on one slot · negative-emotion cues · any regulated topic. The transfer carries a whisper summary (who, what they want, what's been tried, account pulled up) — the caller never repeats themselves; that single property beats every other quality bar in perceived experience.
  6. Score what callers feel, not what dashboards flatter. Containment alone is gameable (trap callers and containment "improves"). The scorecard pairs it with: task success as the caller defines it (post-call yes/no), escapes-requested rate, repair rate, silent-transfer rate, and hang-ups mid-flow. Set launch gates on the pairs.

Output Format

Voice Agent Spec: [line/product]

Intent scope

IntentVolumeOwn / Triage / PassWhy

Opening script: [verbatim — disclosure, capability, escape hatch]

Conversation architecture: [turn rules · confirmation strategy by stakes · the repair ladder (rephrase → options → keypad → human)]

Mechanics: [barge-in behaviour · latency masking thresholds · silence handling]

Handoff: [triggers · whisper-summary fields · after-hours behaviour]

Compliance: [disclosure line · recording consent flow · statements the agent must never make]

Launch scorecard

MetricGateWhy paired
Containment + caller-scored successcontainment alone is gameable
Escape-request ratemeasures trapped callers
Repair rate / hang-ups mid-flowfrustration signals

Quality Checks

  • Every owned intent is completable with the agent's actual system access — no "owns refunds" without refund API access
  • The opening discloses AI status and the escape hatch, verbatim in the spec
  • No designed utterance exceeds two sentences before yielding
  • The repair ladder changes strategy at each rung — no repeat-louder step
  • Handoff carries the whisper summary; "please hold while I transfer you" to a cold human fails the spec
  • The scorecard pairs containment with caller-scored success

Anti-Patterns

  • Do not port the chatbot script to voice — text tolerates paragraphs and menus; ears don't
  • Do not hide the human escape hatch to protect containment metrics — callers find the exit anyway, angrier
  • Do not let the agent bluff on regulated topics (medical, legal, financial advice) — pass or read the approved statement
  • Do not re-ask a failed question unchanged — the caller heard you; the strategy failed, not their ears
  • Do not launch without the mid-flow hang-up metric — it's where voice agents quietly hemorrhage trust

Example Trigger Phrases

  • "Design a voice agent."
  • "Automate a phone line."
  • "Spec an IVR replacement."
  • "Review why callers hate an existing voice bot."

Frequently asked questions

What does the Voice Agent Design AI skill do?

Design a voice AI agent for phone or in-app conversations — call flows, interruption handling, escalation to humans, and the metrics that catch a bad voice experience. Use when asked to design a voice agent, automate a phone line, spec an IVR replacement, or review why callers hate an existing voice bot. Produces a voice agent spec: persona and disclosure policy, conversation architecture, barge-in and repair behaviour, human-handoff rules, and a launch scorecard.

Why use Voice Agent Design on TypingMind?

Because you install it once and use it with any model. Voice Agent Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Voice Agent Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mohitagw15856/pm-claude-skills/tree/main/plugins/pm-agentnative/skills/voice-agent-design. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Voice Agent Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Voice Agent Design?

As many as you like. As long as a model supports skills, you can use Voice Agent Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Voice Agent Design AI skill free?

Yes. It is published on GitHub by mohitagw15856 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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