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.
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.
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SKILL.md
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
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.
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.
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.
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.
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.
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.