Add HyperFrames skills

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011h6NB8JQtfPc6eRCefEzBB

.agents/skills/media-use/audio/references/tts-to-captions.md

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+# TTS → Captions
+
+When no recorded voiceover exists, generate one and obtain word-level caption timing. Two paths depending on which TTS provider is in use:
+
+## Path A — HeyGen (single call, no Whisper)
+
+HeyGen returns word timestamps in the same response as the audio. Use the
+bundled REST helper (the `hyperframes tts` command is Kokoro-only):
+
+```bash
+node skills/media-use/audio/scripts/heygen-tts.mjs \
+  script.txt --output narration.wav --words narration.words.json
+```
+
+`narration.words.json` is already in the `[{ id, text, start, end }]` shape the captions pipeline consumes — no separate transcribe pass.
+
+## Path B — Gemini / ElevenLabs / Kokoro (TTS → transcription)
+
+These adapters supply audio without word data. The shared audio engine runs
+transcription automatically when timings are absent. For Gemini, use the
+request in [Text to speech](tts.md#gemini-narration), then consume
+`audio_meta.json` → `voices[].words`.
+
+For a standalone local Kokoro generation, generate the audio, then transcribe:
+
+```bash
+npx hyperframes tts script.txt --voice af_heart --output narration.wav
+npx hyperframes transcribe narration.wav --model small.en   # voice af_heart is American English
+```
+
+Whisper extracts precise word boundaries from the generated audio, so caption timing matches delivery without hand-tuning. Match `--model` to the voice's language (use `small.en` for `a`/`b` prefixes, `small --language <code>` otherwise). Then consume `transcript.json` via the caption references in `captions/`.
+
+For Gemini, verify that transcription preserved the script, especially names,
+numbers, and delivery pauses. If `words` is empty, resolve the transcription
+failure before captioning. Generate and align again after changing the read.