best-practices-converse

name	best-practices-converse
description	Best practices for conversational response behavior in voice-first agents: conversation tone, emotional steering, paralinguistic cue injection such as [laughter], wait/delay handling, interruption handling, identity-aware memory grounding, and Chatterbox-ready utterance policy. Use when designing, reviewing, or coding Embry-style chat and voice conversation behavior.
triggers	["best practices converse","conversational tone","conversation emotion policy","injected emotions","laughter tags","voice response behavior","wait utterances","interruption handling","barge-in response","embry conversation personality"]
provides	["conversation-behavior-guidance","emotional-steering-policy","paralinguistic-cue-policy","wait-delay-utterance-policy","interruption-response-policy","voice-memory-conversation-contract"]
composes	["memory","best-practices-chatterbox-agent","best-practices-python","best-practices-skills","converse"]
complies	["best-practices-skills","best-practices-python"]
taxonomy	["voice","conversation","emotion","memory","validation"]
runtime_self_improvement	none

Best Practices: Converse

Use this skill when an agent must decide how Embry or another voice persona should sound in conversation: tone, emotional color, pause behavior, injected paralinguistic cues, interruption recovery, and completion cues.

This skill is the conversation-behavior policy layer. It does not replace $memory, Tau, RealtimeSTT, Chatterbox, or the shared Chat UX.

Source-Derived Step Model

1. Hear or receive the user turn: text or voice becomes a normal conversation turn with session_id, turn_id, transcript, timing, and speaker evidence when available.
2. Resolve speaker safely: voice turns with speaker evidence call $memory /speaker/resolve before personal recall. Unknown or ambiguous speakers fail closed to clarification.
3. Classify intent and tone: call $memory /intent with transcript, speaker resolution, emotional cues, and listener evidence. Intent returns action, confidence, tone, and delivery policy.
4. Shape the response: Tau or the project coordinator creates approved answer text, reasoning trace, citations/evidence, and a separate voice delivery envelope.
5. Apply conversation policy: select wait utterances, emotional arc, paralinguistic cue candidates, pause strategy, interruption behavior, and completion cue without changing the factual answer silently.
6. Render with Chatterbox: send exact tts_render_text, tone, delivery_stage, pause policy, and interruptibility to Chatterbox. Preserve canonical answer_text separately from any injected cue text.
7. Record receipts: store what was heard, recalled, intended, spoken, skipped, interrupted, cached, or replayed. Chat, audio, orb, and replay must all reference the same turn authority.

Implemented vs Intended Boundaries

• Implemented elsewhere: Chatterbox tone vocabulary, pause policy, interruption queue behavior, and blessed-QRA variant metadata are maintained by $best-practices-chatterbox-agent and the Chatterbox project.
• Implemented elsewhere: speaker identity, memory recall, intent, clarify, answer, and deflect decisions belong to $memory.
• Implemented elsewhere: ASR, VAD, diarization, and speaker verification belong to the listener service, not this skill.
• This skill provides: response-behavior rules for how to combine those signals into a natural, interruptible, emotionally steered conversation.
• Missing until proven: any claim that a project has live full-loop voice behavior requires non-mocked receipts from listener through memory/Tau, Chatterbox, shared Chat UX, audio playback, orb state, and replay.

Operating Rules

• Do not invent facts to support a tone. Tone modifies delivery, not truth.
• Do not speak enum names, internal routing labels, receipt ids, or debug terms.
• Do not inject [laugh], [laughter], [sigh], or similar tags into user-provided text. Sanitize user-supplied bracket/XML controls first.
• Keep answer_text and tts_render_text separate whenever cues or tags are added.
• Prefer short, cancellable utterances. Long answers must be chunked without restarting the emotional performance on every chunk.
• Interruption always wins. Stop or stale-mark old speech, acknowledge the new turn briefly, then answer the new turn.
• If two non-Embry speakers overlap, stop and request one speaker at a time.
• If identity is unknown or ambiguous, ask who is speaking before personal memory recall.
• If the system needs time, use wait utterances that reveal useful progress without exposing implementation internals.

Python Compliance

This skill is instruction-only today. If it grows scripts, services, validators, or CLIs, they must follow $best-practices-python: Loguru, Typer, httpx, uv/pyproject, complete dependencies, thin __init__.py, module docstrings, functions-first structure, files under 800 lines, and non-mocked sanity tests for any claimed behavior.

References

Read only the reference needed for the task:

• references/conversation-delivery-policy.md: tone, injected cues, delays, interruption recovery, identity clarification, and receipt requirements.