Media operations: agent guidance

media-use resolves and remembers assets. For operating on them: cutting, reframing, stitching, transforming, it does not wrap every action as a bespoke command. Instead it points you at the right local tool (decision OP1). Run the tool, then register the output with resolve --from <output> --type <type> so the result lands in the ledger and the global cache like any other asset.

The ffmpeg and local-model operations below run locally. Direct heygen recipes use the HeyGen CLI's own login and HeyGen/API billing; they do not inherit a HyperFrames subscription. Use those recipes only when that separate payer was selected. hyperframes media-use resolve uses the HyperFrames-selected credential. ffmpeg is assumed present (it backs the engine already).

Cut / trim: keep a slice

ffmpeg -i in.mp4 -ss 00:00:12 -to 00:00:20 -c copy out.mp4   # 0:12–0:20, no re-encode

In-composition trimming usually needs no new file: a clip plays a sub-window via data-media-start + data-duration (see /hyperframes → references/format.md). Only cut a physical file when exporting/assembling outside the composition.

Reframe / crop: change aspect ratio

# 16:9 -> 9:16, crop centered
ffmpeg -i in.mp4 -vf "crop=ih*9/16:ih,scale=1080:1920" out.mp4

For a non-destructive crop, set a clip-path on the element in the composition itself (render-time, source file untouched) instead of re-encoding with ffmpeg.

Montage / stitch: join clips

printf "file '%s'\n" a.mp4 b.mp4 c.mp4 > list.txt
ffmpeg -f concat -safe 0 -i list.txt -c copy out.mp4

Silence-cut / highlight: trim dead air, grab the best moment

auto-editor in.mp4 --edit audio:threshold=4% -o tight.mp4   # pip install auto-editor
scenedetect -i in.mp4 detect-adaptive list-scenes           # pip install scenedetect

Transforms with a quality choice (process)

These have a local option AND a higher-quality HeyGen option. Run the local one for free/offline; use HeyGen when quality matters: media-use generate on the sign-in alone, the rest through the heygen CLI. Showing the user a side-by-side (local vs HeyGen) is the honest way to let them choose.

After any op: resolve --from out.ext --type <type> to register the derived asset (it records provenance and auto-promotes to the global cache).

ponytail: media-use doesn't re-wrap ffmpeg/heygen here, that's deliberate (OP1). The value it adds is the ledger + global reuse on the output, via --from. Add a thin process verb only if agents repeatedly fumble these recipes.

Exact error-diffusion dither

Use the local processor when the requested look specifically calls for Floyd-Steinberg, Atkinson/Macintosh, Jarvis-Judice-Ninke, Stucki, Burkes, or a Sierra variant. These are sequential error-diffusion algorithms, not the realtime Bayer effects.dither shader.

node <SKILL_DIR>/scripts/dither.mjs \
  --input source.mp4 \
  --out source.atkinson.mp4 \
  --algorithm atkinson \
  --palette '#0f380f,#306230,#8bac0f,#9bbc0f' \
  --point-size 3

npx hyperframes media-use resolve \
  --from source.atkinson.mp4 --type video --project .

Available algorithms: floyd-steinberg, atkinson, jarvis-judice-ninke, stucki, burkes, sierra, sierra-lite, and two-row-sierra. The default is balanced Floyd-Steinberg with a black/white palette. Palettes contain 2-6 #rrggbb colors in authored dark-to-light order; reversing the order intentionally inverts the mapping. --point-size controls 1-20px blocks; --brightness and --contrast accept 0.5-2; --detail accepts 0.1-1.

The processor supports ordinary SDR images and MP4 video, preserves video audio, and emits BT.709 MP4. It rejects tagged PQ/HLG input rather than silently tone-mapping it. To animate the transformation, keep the original and processed files as two real media layers and use the seek-safe GSAP timeline to reveal or crossfade between them. Use the realtime Bayer shader instead when the dither amount itself must animate continuously.

Transcription (default: Parakeet, better than whisper.cpp)

transcribe.mjs is the default local transcription path. It runs NVIDIA Parakeet-TDT via parakeet-mlx, which beats whisper.cpp on the Open ASR Leaderboard (avg WER ~6.05% vs 7.44%; on NOISY audio 4.73% vs 5.96%, where whisper-large-v3 hallucinated to 308% WER on meetings) and is 5-10x faster. It emits { text, words:[{text,start,end}] } with word timestamps (merged from Parakeet's sub-word tokens), feeding transcript-cut, captions, and the audio engine directly.

# install once: uv venv ~/.venvs/parakeet && VIRTUAL_ENV=~/.venvs/parakeet uv pip install parakeet-mlx
node <SKILL_DIR>/scripts/transcribe.mjs --input talk.mp4 --out talk.transcribe.json

# the hyperframes CLI runs Parakeet on macOS, Linux and Windows once it is installed:
npx hyperframes models install parakeet                 # once, ~640 MB, ask the user first
npx hyperframes transcribe talk.mp4 --engine parakeet   # or --engine auto (default)

VERIFIED on 24GB: accurate, ~3s (cached) for 8s audio. Parakeet covers 25 European languages, English included. For other languages, or when parakeet-mlx is not installed, transcribe.mjs falls back to hyperframes transcribe, which uses the CLI's Parakeet when models install parakeet has run and whisper.cpp (99 languages) otherwise. --engine parakeet|whisper forces one, except that a --language other than English runs whisper whenever it is installed, since Parakeet detects the language itself. (Cohere Transcribe tops the leaderboard on paper but its mlx-audio quants produced garbage and ran 40-70x slower on a Mac in testing, so it is not wired in.)

Text-based editing (transcript cut)

transcript-cut.mjs is a compiler, not a wrapper: it turns word timestamps and agent cut decisions into exact kept segments. It is provided even though the rest of this file is guidance-only.

node <SKILL_DIR>/scripts/transcript-cut.mjs \
  --input talk.mp4 \
  --transcript talk.transcribe.json \
  --remove "12.41-15.02,88.3-91.7" \
  --remove-fillers "um,uh,like" \
  --cut-silence 0.8 \
  --out talk.cut.mp4

resolve --from talk.cut.mp4 --type video

Use --plan first when you want to inspect the kept segment JSON before encoding.

Ducking (declare in-composition / bake for export)

B1, declare ducking in the composition. audio-duck.mjs emits a volume lane as a data-automation attribute. Add it to the background <audio> element; the source file stays untouched. Lane times are clip-local, so pass --composition to let the script subtract the element's data-start.

node <SKILL_DIR>/scripts/audio-duck.mjs \
  --meta audio_meta.json \
  --target "#bgm" \
  --composition index.html

<!-- auto-duck: #bgm under narration; add to its <audio> element -->
data-automation='{"version":1,"lanes":[{"target":"volume","points":[{"t":0,"v":0.6},{"t":3.42,"v":0.6},{"t":3.57,"v":0.15},{"t":9.87,"v":0.15},{"t":10.27,"v":0.6}]}]}'

B2, bake ducking only for exported or standalone files.

ffmpeg -i bgm.mp3 -i voice.wav \
  -filter_complex "[0][1]sidechaincompress=threshold=0.03:ratio=8:attack=200:release=400[ducked]" \
  -map "[ducked]" bgm.ducked.wav

Declare inside compositions. Bake only for assets leaving the hyperframes pipeline.

Publish loudness

Two-pass loudnorm measures first, then applies the measured values with the target LUFS baked in.

Socials target, -14 LUFS:

ffmpeg -i mix.wav \
  -af loudnorm=I=-14:TP=-1.5:LRA=11:print_format=json \
  -f null -

ffmpeg -i mix.wav \
  -af loudnorm=I=-14:TP=-1.5:LRA=11:measured_I=<input_i>:measured_TP=<input_tp>:measured_LRA=<input_lra>:measured_thresh=<input_thresh>:offset=<target_offset>:linear=true:print_format=summary \
  mix.social.wav

Podcast target, -16 LUFS:

ffmpeg -i mix.wav \
  -af loudnorm=I=-16:TP=-1.5:LRA=11:print_format=json \
  -f null -

ffmpeg -i mix.wav \
  -af loudnorm=I=-16:TP=-1.5:LRA=11:measured_I=<input_i>:measured_TP=<input_tp>:measured_LRA=<input_lra>:measured_thresh=<input_thresh>:offset=<target_offset>:linear=true:print_format=summary \
  mix.podcast.wav

Generate: images (local first, cloud upsell)

resolve --type image retrieves from the HeyGen catalog first; on a miss it GENERATES. Two paths, best-for-the-machine picked automatically:

1. Local (default, free, private): mflux (FLUX-on-MLX). resolve spec-checks AVAILABLE RAM and runs the best FLUX-class model that fits, using the CLI-bundled imagegen ladder (its modules are not shipped in the standalone skill). The RAM ladder:

Gotchas baked into the table: the official FLUX repos are HF-gated, so it points at non-gated community 4-bit re-uploads; and --low-ram is MANDATORY at the medium tier (without it a 768x512 run swap-thrashed to 90 minutes on 24GB; with it, 20 seconds).

1. **Cloud upsell (better quality): the codex CLI** image_gen tool, on the user's ChatGPT subscription (codex owns auth, no key here, no per-call charge). It is the automatic fallback when no local model fits AND the explicit "make it better" choice on any machine. Users who just want codex can ask for it directly. Verified: prompt -> raster -> frozen + ledgered.

--local-only keeps mflux (once cached) and skips codex (network).

Generate: video (resolve --type video, HeyGen avatar first)

resolve --type video "<intent>" is the default path. It generates a script-driven HeyGen avatar video first using the HyperFrames-selected credential (the server decides eligibility and charges; explicit API keys use API billing), falling back to local generative LTX only when HeyGen is unavailable, uncredentialed, or --local-only is passed. The two are non-substitutable outputs (a real presenter vs. a generic generative clip), so treat the fallback as "HeyGen wasn't reachable," not "upgrade the quality":

• HeyGen avatar video (default): The CLI-bundled provider shells the heygen CLI — never the raw API — auto-picking a public avatar and a starfish voice (override with --avatar-id/--voice-id, threaded through as ctx.avatarId/ctx.voiceId). If the CLI reports not_authenticated, the provider prints a HyperFrames sign-in recommendation to stderr and falls through to LTX instead of hard-failing.
• Local fallback: LTX 2.3 on MLX via dgrauet/ltx-2-mlx, the videogen ladder bundled in the HyperFrames CLI. Generative clips (t2v), spec-gated to RAM. Verified on 24GB: 512x320 x 33f with audio.

Every generating heygen call from media-use — TTS, avatar video, and catalog search — sends the allowlisted X-HeyGen-Client-Source: media-use header (persistent flag, works on every subcommand) via the shared CLI-internal HEYGEN_CLIENT_SOURCE_ARGV constant, so usage tags correctly in billing/resource meta and shows up in the API dashboards. Read-only discovery (avatar list, voice list) doesn't need it.

For structured bodies resolve --type video doesn't expose yet (a specific avatar_id/voice_id combination beyond the ctx overrides, or a pre-recorded audio_url instead of a script), the raw heygen video create recipe below remains the escape hatch. This direct command uses the separate HeyGen CLI credential and HeyGen/API billing, not the HyperFrames subscription:

# discover an avatar + a starfish voice, then create + wait
heygen avatar list --ownership public --limit 5
heygen voice list --engine starfish --limit 5
heygen video create --headers "X-HeyGen-Client-Source: media-use" --wait -d '{
  "type": "avatar",
  "avatar_id": "<avatar-id>",
  "script": "Your narration here.",
  "voice_id": "<voice-id>"
}'

Avatar videos are deterministic + script-driven (lip-sync from a script or a pre-recorded audio_url), distinct from the generative LTX clips. After a manual recipe renders, resolve --from <downloaded.mp4> --type video to ledger it (not needed when generating via resolve --type video directly — that already ledgers the result).

Image-to-video (animate any still into a talking clip)

Not wired into resolve --type video (deferred — the avatar type covers the default script-driven case). heygen video create takes the raw POST /v3/videos body, so switching type from avatar to image animates any image of a person into a lip-synced talking video, with no avatar/photo-avatar creation step first. Point image at a public URL or an uploaded asset_id, and drive speech with a script+voice_id or a pre-recorded audio_url:

heygen video create --headers "X-HeyGen-Client-Source: media-use" --wait -d '{
  "type": "image",
  "image": { "type": "url", "url": "https://example.com/person.jpg" },
  "script": "Your narration here.",
  "voice_id": "<voice-id>"
}'

Common optional fields: title, resolution (4k/1080p/720p), aspect_ratio, remove_background, background, voice_settings, motion_prompt + expressiveness (photo-avatar animation), and callback_url/callback_id for webhooks. Don't hardcode these from memory: the CLI self-documents the full, current body with heygen video create --request-schema (a discriminated union keyed on type), so read the schema rather than trusting a stale field list. For a still you'll reuse across many scripts, create a reusable Photo Avatar once instead (heygen avatar create). Ledger the result with resolve --from <downloaded.mp4> --type video. Docs: <https://developers.heygen.com/image-to-video>.

HEVC / H.265 sources

HEVC/H.265 sources need no conversion for render (FFmpeg pre-decodes all input video) or for preview (auto-proxy transcodes and caches an H.264 copy on first use, disable with --no-proxy or media.autoProxy: false in hyperframes.json). A manual H.264 proxy via ffmpeg -i in.mp4 -c:v libx264 -crf 18 proxy.mp4, registered with resolve --from, remains available for edge cases (e.g. auto-proxy disabled, or ffmpeg unavailable at preview time).