audio-explainer

Trigger refinements

ALSO FIRE when the user drops a YouTube / podcast URL whose duration is > 4 minutes AND asks for "a video" (not "a clip" / "a short" / "a cut") — that is the audio-to-longform path, not the short-form cut path. Long-form on a URL: pull --audio-only, then run this skill on the audio.

DO NOT FIRE for:

• Short-form cuts (< 4 min) from a long-form source — route to podcast-clip template.
• Talking-head essays where the user wants their face on screen — route to yap-talking-head or green-screen-explainer.
• Multi-speaker debates / interviews — route to interview-dialog (split-screen) or podcast-clip (cut viral moments).
• Music videos / non-speech audio — route to music-video template.
• Once the project has index.html composed and the user wants render / preview tweaks — handback to the editor playbook.

Hard invariants

1. ralphy is the only entry-point. No direct ffmpeg, yt-dlp, curl, or bunx tsx against provider SDKs. Every step in the workflow below is either a ralphy verb (already shipped) or an LLM call routed through cli/lib/providers/llm.ts → callLLM(). AGENTS invariant #2.
2. Append-only on the project dir. Per AGENTS invariant #14, every regeneration writes .v2 / .v3 files. Never overwrite overlay-plan.json, captions.json, or any asset in artifacts/. The skill writes a new version; the user picks which to promote.
3. English-only on disk. Every file the skill writes lands in English. If the source audio is Russian / Spanish / etc., the on-disk overlay-plan.json keeps vo_text in the source language (it's transcript content) but every comment, log line, file name, and skill-generated annotation is English. Chat with the user matches their language.
4. No raw API code. Browser screenshots run through a Playwright helper script the skill calls via bunx playwright, not via raw puppeteer.launch() in inline code. Image generation goes through ralphy generate image. Music + SFX through ralphy generate music + ralphy generate sfx. No direct ElevenLabs HTTP calls.
5. Composition must be deterministic. The HyperFrames index.html the skill emits has no Date.now() / unseeded Math.random() / fetch() at render time. Per docs/playbooks/hyperframes.md hard invariants.

---

What this skill is

A one-shot orchestrator that turns audio into a long-form faceless video. The contract: the user drops an audio source and a one-line topic gloss; the skill returns a rendered mp4 (or, if the user wants to iterate, a composed index.html ready for bunx hyperframes preview).

The skill is the editorial brain that the routing table in AGENTS.md points "audio podcast → faceless overlay video" requests to. It does not introduce new CLI verbs — every step it runs is an existing primitive.

What this skill is not

• Not a short-form cutter. Use the podcast-clip template for ≤ 60s viral cuts.
• Not a translator / dubber. If the user wants to re-narrate the audio in another language, that is a separate podcast-dub workflow (different pipeline, voice cloning).
• Not a publisher / uploader. Output is .ralphy/workspaces/<ws>/projects/<id>/render/final.mp4. The user uploads it themselves.

The workflow

[audio source]                  [topic gloss]
      │                              │
      ▼                              ▼
   step 1                         step 1
   pull/copy audio              (recorded in
   into project                  ralphy new
                                  prompt)
      │
      ▼
   step 2 — silence-remove pass on the VO track
      │ (ffmpeg recipe via cli/lib/ffmpeg-recipes.ts; until
      │  `ralphy audio remove-silence` ships, the skill calls
      │  the recipe lib directly through a thin tsx wrapper —
      │  see notes/ideas/007.)
      ▼
   step 3 — word-level transcript (`ralphy generate captions`)
      │
      ▼
   step 4 — audio describe (`ralphy ref audio-describe`)
      │
      ▼
   step 5 — claim segmentation + chapter detection (LLM)
      │
      ▼
   step 6 — overlay-type assignment (LLM, rule-driven prompt)
      │
      ▼
   step 7 — emit overlay-plan.json
      │
      ▼
   step 8 — asset prep (per overlay type)
      │       • screenshots → Playwright helper
      │       • memes / images → `ralphy generate image`
      │       • logos → curated set or generate
      ▼
   step 9 — music bed (`ralphy generate music`)
   step 10 — SFX set (`ralphy generate sfx` × 3)
      │
      ▼
   step 11 — emit index.html + compositions/chapter-NN.html
      │
      ▼
   step 12 — `ralphy editor preflight` && `ralphy render`

Each step writes to .ralphy/workspaces/<ws>/projects/<id>/. Re-running the skill detects existing artifacts and skips them (idempotent), matching the researcher resume pattern.

Step-by-step

Step 1 — ingest the audio

# Create the project from the topic gloss
ralphy new "long-form faceless explainer from audio about <topic>"
# → .ralphy/workspaces/<ws>/projects/<id>/

# If the source is a URL:
ralphy ref pull "<url>" --slug <ref-slug> --audio-only
cp .ralphy/references/<ref-slug>/source.mp3 \
   .ralphy/workspaces/<ws>/projects/<id>/artifacts/refs/source.mp3

# If the source is a local file:
cp /path/to/podcast.mp3 .ralphy/workspaces/<ws>/projects/<id>/artifacts/refs/source.mp3

Step 2 — remove dead air

# Until `ralphy audio remove-silence` ships (see notes/ideas/007),
# the skill calls the ffmpeg recipe directly via:
bunx tsx -e 'import { removeSilence } from "./cli/lib/ffmpeg-recipes"; …'
# Threshold: -40 dBFS, min silence 0.6s.
# Output: .ralphy/workspaces/<ws>/projects/<id>/artifacts/audio/vo.mp3 (silence-removed)
#         .ralphy/workspaces/<ws>/projects/<id>/cut-map.json (original_t → trimmed_t)

The cut-map.json is informational; transcript timestamps are recomputed from the trimmed audio in step 3, not via remapping.

Step 3 — transcribe (word-level)

ralphy generate captions \
  --audio .ralphy/workspaces/<ws>/projects/<id>/artifacts/audio/vo.mp3 \
  --out  .ralphy/workspaces/<ws>/projects/<id>/captions.json

Verify the output has per-word start / end. ElevenLabs Scribe v1 returns word-level for all supported languages — if the JSON is sentence-level only, surface a hard error.

Step 4 — audio describe

ralphy ref audio-describe <ref-slug>     # if pulled from URL
# OR — if the source was a local file, run the equivalent
# `ralphy generate` LLM call over the mp3 via callLLM().

Read audio-analysis.json to set the music-bed style + emphasis-detection sensitivity.

Step 5 — claim segmentation + chapter detection

LLM pass (default model: anthropic/claude-sonnet-4-6 via OpenRouter — confirm against MODELS.md).

Prompt input: captions.json + audio-analysis.json.

Prompt instructions (skill emits them inline; do not paraphrase):

• Group words into claim blocks (2-8s each, target 4s, break on punctuation + pause > 350ms).
• Group claims into chapters (60-180s each, break on pause > 1.5s or discourse cue).
• Each chapter gets a 3-5 word name.
• Output strict JSON: [{ chapter, chapter_name, claims: [{ start, end, vo_text }] }].

The full prompt template lives in references/segmenter-prompt.md.

Step 6 — overlay-type assignment

Second LLM pass. Input: the segmented claims from step 5 + the topic gloss.

Prompt instructions:

• For each claim, pick exactly one overlay type from the fixed vocabulary in templates/creator-lifestyle/podcast-explainer-longform/prompt-cookbook.md § "Step 3 — assign overlay type".
• For each chosen type, emit the content shape specified in the cookbook.
• Apply rate-limits: ≤ 1 logo-pop per chapter unless the brand is the chapter topic. ≤ 2 meme per chapter. quote-card-kinetic reserved for punchlines (LLM-rated as high-emphasis) — ≤ 1 per chapter.
• Output: full overlay-plan.json matching the schema in the cookbook.

Step 7 — emit overlay-plan.json

Write to .ralphy/workspaces/<ws>/projects/<id>/overlay-plan.json. If the file already exists, write overlay-plan.v2.json and show the user a diff summary. Never overwrite.

Step 8 — asset prep

Iterate overlay-plan.json. For each entry:

• code-block / terminal / tweet-card / quote-card-kinetic / chapter-card / diagram → composition-time render, no asset prep needed.
• browser-frame → run a Playwright capture helper: bunx tsx scripts/capture-screenshot.ts --url <url> --out artifacts/screenshots/<slug>.png. (Helper script lives in the skill's scripts/ folder.)
• screenshot / meme / logo-pop (when not in the curated set) → ralphy generate image --project <id> --slot <id> --prompt "<content.image_prompt>".

Failed generations: do not retry blindly. Log the failure, mark the overlay slot with status: "failed", surface the count to the user with a one-line summary at the end.

Step 9 — music bed

# Read total duration from captions.json (last word's `end` value + 5s)
ralphy generate music --project <id> \
  --duration <total> \
  --style "lo-fi ambient electronic instrumental, 75-85 BPM, ..." \
  --instrumental \
  --out artifacts/audio/music.mp3

The full prompt template is in the cookbook. Style override (lo-fi / ambient / cinematic) comes from the user or, if absent, from audio-analysis.json (high-energy VO → cinematic; calm VO → lo-fi).

Step 10 — SFX set

ralphy generate sfx --project <id> --label whoosh \
  --prompt "fast tape whoosh transition, 0.4s, dark and short"
ralphy generate sfx --project <id> --label pop \
  --prompt "soft UI pop click, 0.1s, glassy and dry"
ralphy generate sfx --project <id> --label hit \
  --prompt "deep sub-bass hit, 0.6s, cinematic punchline"

Three files at artifacts/audio/whoosh.mp3 / pop.mp3 / hit.mp3.

Step 11 — compose HTML

Emit index.html + compositions/chapter-NN.html matching the skeleton in templates/creator-lifestyle/podcast-explainer-longform/composition.md. The skill walks the overlay plan and writes one <div class="clip"> per overlay, inlining the per-type fallback HTML (since the registry blocks are not yet upstream — see notes/ideas/006).

Captions are injected as a paused GSAP timeline that tl.set()s the caption layer's innerHTML at each chunk boundary. Chunk boundaries are computed at compose-time from captions.json per the rules in the cookbook (8-15 words, break on punctuation).

Step 12 — preflight + render

ralphy editor preflight <id>
ralphy render <id> --aspect 16:9 --loudnorm

Final output: .ralphy/workspaces/<ws>/projects/<id>/render/final.mp4. Show the user the path and the file size. Suggest ralphy eval video <path> for a quality gate before publishing.

Inputs / outputs contract

Inputs the user provides:

1. Audio source (file path OR URL).
2. Topic gloss (one sentence).
3. Optional flags: --aspect, --theme, --music-style, --opener.

Outputs the skill leaves on disk:

• .ralphy/workspaces/<ws>/projects/<id>/captions.json
• .ralphy/workspaces/<ws>/projects/<id>/overlay-plan.json (the editorial decision record — preserve forever)
• .ralphy/workspaces/<ws>/projects/<id>/artifacts/audio/{vo,music,whoosh,pop,hit}.mp3
• .ralphy/workspaces/<ws>/projects/<id>/artifacts/{screenshots,memes,images,logos}/*
• .ralphy/workspaces/<ws>/projects/<id>/index.html + compositions/chapter-NN.html
• .ralphy/workspaces/<ws>/projects/<id>/render/final.mp4
• All generations logged to .ralphy/workspaces/<ws>/projects/<id>/logs/generations.jsonl.

Handoff

When the user wants to iterate on a specific chapter or overlay choice, handback to the editor playbook with a pointer to the offending chapter / overlay id. The editor handles re-composition and re-render without re-running the segmentation.

If the user wants to evaluate the final mp4, route to /evaluator.

References

• templates/creator-lifestyle/podcast-explainer-longform/ — the template the skill targets.
• references/segmenter-prompt.md — the claim-segmentation LLM prompt.
• references/overlay-assigner-prompt.md — the overlay-type-assignment LLM prompt.
• scripts/capture-screenshot.ts — Playwright helper for browser-frame overlays.
• docs/playbooks/hyperframes.md — composition rules, GSAP timelines, registry blocks.
• docs/playbooks/editor.md — render / preflight / iteration handback.
• MODELS.md — segmentation + planner model defaults.
• notes/ideas/006-hyperframes-overlay-blocks.md — upstream HyperFrames block contributions.
• notes/ideas/007-ralphy-audio-remove-silence.md — the missing CLI verb the skill works around for now.