story-narrator

name

story-narrator

description

Generates one expressive narration MP3 per scene for an English storybook, using the ElevenLabs MCP (text_to_speech). Reads {slug}_scenes.json (from scene-splitter), proposes a warm storyteller voice, drafts the narration text per scene (optionally with Eleven v3 audio tags for emotion), lets the user review, then generates one MP3 per scene saved as {slug}_part_NN.mp3 so it pairs by index with the scene's image. Use this skill whenever the user wants to narrate a story, generate per-scene audio, voice a storybook, create read-along narration, or produce TTS for the storybook pipeline. Trigger on phrases like "narrate this story", "generate the audio", "voice the storybook", "make the narration", "read this story aloud", or whenever scenes.json exists and the user wants spoken audio. Requires the ElevenLabs MCP connected.

Story Narrator

Turns a story (already split into scenes) into a set of expressive narration clips — one MP3 per scene — using the ElevenLabs MCP. Each clip is saved as {slug}_part_NN.mp3 so it pairs by index with the scene's image: scene 3's picture and scene 3's narration play together in the final storybook.

When this skill applies

{slug}_scenes.json exists (from scene-splitter) and the user wants per-scene audio. Also applies if the user pastes a story and asks to narrate it — split it first (or narrate paragraph-by-paragraph).

The skill does NOT apply to:

• A single short utterance (call text_to_speech directly).
• Real-time conversational TTS, music, or sound effects.
• Voice cloning (do that separately in ElevenLabs, then bring the voice_id here).

Required tool — the ElevenLabs MCP

The skill calls mcp__elevenlabs__text_to_speech. Confirm it's available before Stage 4. If the MCP isn't connected, tell the user to install it (uvx elevenlabs-mcp with ELEVENLABS_API_KEY set — see https://github.com/elevenlabs/elevenlabs-mcp) and stop. Stages 1–3 (voice choice + narration script) work without it; only generation needs it.

Key text_to_speech parameters this skill uses:

• text — the scene's narration text
• voice_id (or voice_name) — the chosen storyteller voice
• model_id — see Stage 2 (default a v3 model for audio-tag expressiveness; fall back to eleven_multilingual_v2)
• stability — 0.4–0.5 for natural, expressive delivery (lower = more emotional range)
• style — small positive value (e.g. 0.2) adds expressiveness; 0 is flat
• output_directory — set to the story's audio folder so files land in the right place

The MCP saves the file and returns its path — it names the file itself, so this skill renames each result to the locked {slug}_part_NN.mp3 convention after generation (Stage 5).

Workflow — five stages with one hard gate

Stage 0: Load scenes.json

Read {slug}_scenes.json. Treat each scene's text as one narration clip. Use each scene's mood to guide delivery/tag choices. The clip for scenes[i].index = N becomes {slug}_part_NN.mp3.

Stage 1: Intake and analysis

1. Read all scene texts.
2. Note total characters (rough cost = chars × ~$0.10/1k) and how much is dialogue.
3. One-line summary: "N scenes, ~C total characters, ~D% dialogue. Recommendation: single narrator."

Stage 2: Voice strategy and selection

Propose single narrator (the default and best choice for beginner storybooks — one warm voice carrying the whole story, shifting tone for dialogue). Only consider per-character voices if dialogue is heavy AND there are 2+ distinct recurring speakers AND their voices should clearly differ — and even then, single narrator usually sounds more cohesive for a short children's story.

Voice choice:

• If the user already has a preferred voice_id, use it.
• Otherwise, suggest finding a warm, friendly storyteller voice. You can call mcp__elevenlabs__search_voices (e.g. search "storyteller" or "warm narration") and propose ONE specific voice with its voice_id. Don't list five.
• Ask once if needed: "What voice_id should I use? (Find one in your ElevenLabs library, or I can search for a warm storyteller voice.)" Suggest the user save it for future runs.

Model choice:

• Default to eleven_v3 (most expressive; supports [warmly]-style audio tags). If the account/MCP doesn't support v3, fall back to eleven_multilingual_v2 (no audio tags — rely on stability/style for expressiveness). State which one you're using.

Pause: "Voice: [name + id]. Model: [v3 / multilingual_v2]. Single narrator. Reply go, or tell me what to change."

Stage 3: Narration script (+ optional emotion tags)

For each scene, prepare the narration text:

• original — the scene's text, unchanged
• tagged — only if using eleven_v3: the same text with a few audio tags inserted to match the scene's mood. Use sparingly (1–2 tags per scene). Useful tags: [warmly], [softly], [gently], [cheerfully], [curiously], [whispering], [excited], [sadly], [reassuringly]. Place a tag BEFORE the text it affects; it persists until the next tag. Use ... for natural pauses. Don't over-tag — it reads choppy.
  • If using eleven_multilingual_v2, skip tags entirely (it ignores them / reads them aloud). Expressiveness comes from stability/style and the voice itself.
• rationale — one line on why those tags fit (only when tagging)

Title clip (recommended). Produce a short separate title.mp3 from the bare story title with one warm tag ([warmly] The Little Cloud.). The publisher plays it on the dedicated cover page (slide 0) before auto-advancing into scene 1, so the cover isn't silent — generating it is worth the one extra clip. Keep it minimal. Save it as {slug}_audio/title.mp3.

Write the full script to {slug}_audio/narration_script.md (one ## Scene NN section per scene with the subsections above) so the user can review it in one place.

Stage 4 — HARD GATE: review the narration script

Show the script and pause: "Narration script ready — review before I generate audio. Each generation is billed (~$0.10/1k chars) and non-deterministic, so a bad script wastes credits. Reply go to generate, edit for changes, or paste a corrected version."

Do NOT proceed without explicit approval. If the user wants changes: minor wording → update and re-show; "less excited / more intimate" → re-tag with the new direction; "redo scene X" → update just that scene.

Stage 5: Generate audio (one MP3 per scene)

For each scene, call mcp__elevenlabs__text_to_speech with:

• text = the scene's tagged text (or original if not tagging)
• voice_id = chosen voice
• model_id = chosen model
• stability = 0.45, style = 0.2, use_speaker_boost = true (tune to taste)
• output_directory = stories/{slug}/{slug}_audio/

The MCP saves the file and returns its path. Rename the saved file to {slug}_part_NN.mp3 (zero-padded scene index) — use the Bash tool (mv) so filenames match the locked convention. If a generation fails, capture the error and continue with the rest of the scenes — don't crash the batch.

Leading-punctuation gotcha (Windows). The MCP derives the saved filename from the first characters of the text, so if a scene's text begins with a quote (") or other character invalid in a filename, the save fails with [Errno 22] Invalid argument even though the audio generated (and you're billed). Workaround: send that scene's text with the leading quote stripped — ElevenLabs doesn't voice quotation marks, so the spoken audio is identical. (Quotes inside the text are fine; only the first character matters for the filename.)

If you produced a title clip, generate it the same way and rename it to title.mp3.

After all scenes:

• Write {slug}_audio/manifest.json listing each clip: index, filename, original, tagged (if any), and the scene's mood/scene metadata. Include a title_audio entry if a title clip was made.
• Report: number of clips generated, approximate cost (total chars × $0.10/1k), any failures with the scene index for retry, and the audio folder path.

{
  "story_slug": "the-little-cloud",
  "voice_id": "...",
  "model_id": "eleven_v3",
  "title_audio": { "filename": "title.mp3", "original": "The Little Cloud", "tagged": "[warmly] The Little Cloud." },
  "parts": [
    { "index": 1, "filename": "the-little-cloud_part_01.mp3", "original": "High in the sky...", "tagged": "[warmly] High in the sky...", "mood": "gentle, bright" }
  ]
}

After Stage 5

The skill is done — one MP3 per scene plus a manifest, ready for the publisher. To redo specific scenes: "regenerate scenes X, Y" — generation is idempotent on filenames, so reruns overwrite cleanly. Or edit the script first and regenerate just those scenes.

Cost expectations

ElevenLabs v3 is ~$0.10 per 1,000 characters. A short beginner story (~1,500–2,500 chars across all scenes) costs ~$0.15–$0.25 once. Audio tags add ~5–10% character overhead. Budget for 1–2 regenerations of some scenes since v3 is non-deterministic — the Stage 4 gate exists to get the script right before spending on audio.

What this skill does NOT do

• Does not edit the story text — tags are added; the prose itself doesn't change.
• Does not generate music or sound effects — only narration.
• Does not do voice cloning — bring a voice_id from ElevenLabs' separate workflow.
• Does not QA the generated audio — listening and approval is the user's job.

Compatibility notes

• Eleven v3 supports audio tags ([warmly]); eleven_multilingual_v2 does not — match your tagging to the model.
• Eleven v3 does not reliably support SSML <break>; use ... for pauses.
• v3 is non-deterministic — the same input can produce different audio across runs. The Stage 4 gate is the cost-control valve.
• Filenames MUST end up as {slug}_part_NN.mp3 (and optionally title.mp3) so the publisher pairs audio with images by scene index.