#I use dinamic variables (collected at Initiation Data request), and I the HTTP body I construct the

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orchid terraceBOT
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AI-generated Answer for digi_tall.

Short answer: yes—natural, “non‑robotic” delivery and good reasoning come from the combination of your prompt/context (including dynamic variables) plus the TTS voice and its settings.

What the docs confirm

  • You can pass conversation initiation data that includes both dynamic_variables and conversation_config_override. The override can change the agent prompt/first message/LLM and TTS fields like voice_id. (elevenlabs.io)
  • Overrides currently support voice_id, stability, speed, and similarity_boost for TTS. Style is not listed among overridable fields in Agents; if you need style, change the voice’s settings at the voice level via the Voices API. (elevenlabs.io)
  • Dynamic variables are the recommended way to personalize prompts and tool calls; they’re injected at start (for prompts) and kept up to date for tools. (elevenlabs.io)

What affects “intonation” (prosody) and perceived naturalness

  • Stability: Lower values introduce a broader emotional range; higher values can sound more monotonous. This is often the first knob to reduce “robotic” delivery. (elevenlabs.io)
  • Speed: Keep near 1.0; the supported range is roughly 0.7–1.2, and extreme values can degrade quality. (elevenlabs.io)
  • Similarity boost and Speaker boost: Increase adherence to the reference voice; speaker boost can add latency. Use judiciously. (elevenlabs.io)
  • Style (voice-level setting): Controls style exaggeration and may add latency when >0. Adjust via the Voices API if needed. (elevenlabs.io)
  • If output sounds too monotone or chaotic, ElevenLabs recommends tweaking voice settings and notes that different voice types vary in emotional range. (help.elevenlabs.io)
  • TTS is non-deterministic; sliders define ranges rather than fixed outcomes, so expect to iterate. (elevenlabs.io)

What affects “smartness”

  • Your LLM choice, system prompt, knowledge base, and tools drive reasoning quality; the Agents Platform composes ASR + LLM + TTS + turn‑taking. Use overrides/dynamic variables to supply the right context, and a knowledge base/tools for grounding. (elevenlabs.io)

Bottom line: your approach—feeding dynamic variables into the system prompt and selectively overriding voice settings—matches how ElevenLabs intends agents to be personalized. Tune stability/speed/similarity (and style via the Voices API if needed), while iterating on prompts and context, to reach natural

last herald
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Soo ... OK, it means I just "suck" at constructing the system prompt.
Any tips and tricks for a "fixed" conversation?

orchid terraceBOT
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AI-generated Answer for digi_tall.

Here are the levers ElevenLabs documents for making an Agent feel natural and stay on‑script in a “fixed” conversation:

  • Use the System prompt and First message to set behavior, style, and opening line. The system prompt directly controls the agent’s demeanor; pair it with a constrained knowledge base if you need tighter scope. RAG can further focus answers if you add source docs. (help.elevenlabs.io)
  • Pick the right model for conversational use. For real‑time/voice agent flows, use v2.5 Turbo or Flash; v3 (Alpha) is more expressive but not recommended for real‑time conversations due to reliability/latency. (help.elevenlabs.io)
  • Tune delivery with voice Speed. Set speed between 0.7 and 1.2; extremes can degrade quality. This is available in Agents and TTS. (help.elevenlabs.io)
  • Add natural pauses. In TTS/Agents, use SSML <break time="Xs" /> (up to 3s) for consistent, natural pauses; don’t overuse to avoid artifacts. If you generate with v3 specifically, use its pause tags instead. (help.elevenlabs.io)
  • Ensure clean pronunciation and intonation.
    • Specify language via API with language_code for short/ambiguous text. Choose a voice trained on that language/accent for better pronunciation/intonation. (help.elevenlabs.io)
    • For numbers, dates, acronyms: either have the LLM spell them out in words or enable text normalization (apply_text_normalization) when using the API. (help.elevenlabs.io)
  • Keep responses “fixed” by limiting what the model can reference. Populate an Agent knowledge base with only the content you want it to use; enable RAG to bias answers toward those documents. Mind size limits and the 500‑byte minimum per item for RAG. (help.elevenlabs.io)
  • Orchestrate the flow with Tools. System Tools let you end or transfer calls or switch languages at defined points. Webhooks can call your own APIs to fetch/update state as the conversation progresses. (help.elevenlabs.io)
  • If something goes off, check Call History. It surfaces issues such as “Missing required dynamic variables …” or “Override is not allowed for this AI agent,” which commonly block
last herald
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Rules on how to construct the system prompt?