ghost-editor

name: ghost-editordescription: "AI video editor for talking-head reels. Turns a raw phone recording of someone talking to camera (retakes, pauses, false starts) into a finished vertical 1080x1920 reel for Instagram, TikTok or Shorts: the best take of each sentence, pause trimming, word-timed captions that never cover the face, motion scenes on the spoken word, sound effects mixed against the voice and checked B-roll. Use when the user hands over a talking-head video and says \"edit this\", \"make a reel\", \"make it look like this video\", \"add captions/sound effects\", \"pick the best takes\", \"remove the pauses\", asks for a re-cut, or names a style. Named styles (recipes/, docs/PLAYBOOK.md): Clean OS, Seoul list, RESULT, Face RESULT, stan style, vector explainer, POV montage, Whiteboard, Kinetic doc, Step Deck, Product page, Tactile paper, Caption News, News Package, Telestrator, Halftone Dossier, Swiss Grid, Data Story, Hologram HUD; plus seven presets (clean, editorial, meme, cinematic, launch, kinetic, pop). Not for landscape screen recordings."

ghost-editor

One recording in, one reel out. The creative work is choosing takes and planning beats. The scripts do everything else the same way every time: cut math, zoom tweens, captions, SFX levels, asset copying, QA. Nothing on screen says anything the speaker did not say. A meme is a reaction, so it lands ON or just AFTER the punchline, never before it.

Skill dir: ~/.claude/skills/ghost-editor (below: $S). A reel project is any directory ($P); build.mjs copies what it needs into $P/assets so the project renders on its own.

Cost: one fresh helper per reel, the right model per step

Measured on a batch of 21 reels: looking at frames was ~5 % of the Claude usage. The cost is context re-read on every turn (one helper that built 3 reels in a row re-read 212 M cached tokens over 464 turns) and new generator code written per reel (two helpers per style each wrote their own lib). Numbers: docs/PLAYBOOK.md "Cost".

• One reel = one FRESH helper (Agent tool). Never one helper for several reels or a wave. The session that talks to the user orchestrates: fill templates/briefs/build-one-reel.txt (build -> preview -> stop), send them the preview, and on their OK fill templates/briefs/finish-one-reel.txt for a new helper. Changes after their notes go to a fresh helper with the reel's reel.py and their words (the generator is the state, not the old transcript); SendMessage the old helper only for a one-line fix. Spawn helpers as reel-helper when the session lists it (templates/agents/reel-helper.md, copied to ~/.claude/agents/; shell and file tools only): a general-purpose helper starts at ~85 k tokens of tool and skill lists and re-reads them on every call. Long jobs run in one blocking call, never a background job polled per turn.
• Model per step: Opus (the default) plans and judges: takes, hook, beats, components, reel.py, snapshots, the user's notes. Sonnet (Agent tool model: "sonnet") runs fixed recipes: preview / final renders, finals.py qa / deliver, components.py record, file moves and commits. It stops on a hard QA fail and reports; the fix goes back to Opus. Many frames are Gemini Flash's job (broll_vision / broll_qa), not Claude's.
• Little code per reel: a named style's reel is a short generator on its recipe's builder (clean-os/cleanos.py + kit.py, result-podcast/faceresult.py, whiteboard/board.py, seoul-list/seoul.py); read <builder> --api, not old generators, and never write a per-batch lib. A part two reels needed goes into the builder's kit.
• Small context: grep / sed -n, not cat; one overview sheet per look (snap.py beats -> overview.jpg), not single frames; never re-read what you just wrote. Measure a reel with scripts/reel_usage.py <helper transcripts>.

Pipeline

prep.sh        -> $P/assets/talk.mp4        1080x1920 30 fps, voice at -16 LUFS
transcribe.py  -> $P/build/words.whisper.json + take table (all takes)
face_track.py  -> $P/build/face.json          (captions and cards never cover the face)
choose takes   -> $P/reel.json takes        (references/take-selection.md)
  a scripted recording with many takes: rawcut_prep.sh -> vad_pauses.py -> islands_tx.py -> facescan.py --pts -> takes.py -> plan_cut.py -> subcheck.py
  -> assemble.py --plan -> voice_smooth.py --plan -> qa_cut.py: the clean raw cut every style builds on (take-selection.md)
plan beats     -> $P/reel.json beats/zoom   (references/reel-json.md; taste.py prompt first)
film_look.py / transitions.py reel           optional: graded plate, transition windows (after takes are final)
build.mjs      -> $P/index.html             + SFX table + rule and taste warnings
approval_sheet.py -> build/approval.html    lint, a frame at every cut and beat; WAIT for the user's yes
own_footage.py -> the user's own clips for the lines (face-checked: only them); `sheet` -> show the picked frames, WAIT for yes
broll_fetch.py -> $P/broll/: stock originals (Pexels by link, Mixkit search) + manifest.json; when to use which: references/broll.md 3
pictures: wikimedia_fetch.py (archival first) -> google_images.py; EN + RU, >= 1080 px, people-checked (references/broll.md 3)
brand_kit.py pull <tool URL> --dir $P/brand -> a reel about a named tool/app/company: its real logo (light + dark), icon, brand colour, nearest Cyrillic Google font, people-checked product shots; LOOK at brand/sheet.jpg
image_pick.py brief/pull/score/pick/sheet -> per line 6-10 candidates scored 0-5 (says the line at a glance >= 4 or FLAG); the scores sheet goes next to the preview
insert_prep.py -> every B-roll insert: people + line check, cut, SDR, fps conform, graded onto the speaker's plate as shot (never the reverse)
components.py plan/check -> new components per reel for a named style (catalog.json); record after the user's yes
broll_vision.py picks -> build/broll-picks.jpg: every B-roll shot + stock image, its line, the people check; WAIT for the user's yes
finals.py preview -> "<name> (preview).mp4": 720x1280 at ~4.5 Mbit/s for the user's phone (+ a frame-0 still); WAIT for their OK
finals.py render  -> "<name>.mp4": delivery master -> Instagram H.264 (refuses a reel with no current preview)
finals.py qa      -> render_report.py + broll_qa.py per reel, one summary line each; fix and re-render, at most 3 rounds
qa.py             -> SFX-vs-voice on a stem, A/V lengths, contact sheet
finals.py deliver -> optional: -14 LUFS into the user's library of finished videos (CONTENT): NOT POSTED, _moves.tsv,
                     TRACKER; taste.py log-reel; save_style.py if the user loved it

0. Check the toolchain once per session

bash $S/scripts/doctor.sh: tools, GEMINI_API_KEY and the media library, each with its fix. The Gemini key is needed for the B-roll checks (the free tier is enough), and doctor proves it with one test call: insert_prep.py, broll_vision.py and broll_qa.py's people / match checks ask Gemini, and with people rules set a shot nobody could check fails the QA. On a fresh machine run python3 $S/scripts/library_restore.py first (SFX, memes, music and the animated emoji aren't in git). Say what is missing; don't improvise around it. Lines marked opt are optional tools with their own scripts/setup_<x>.sh (BiRefNet matte, audio QA, film-look LUTs, caption metrics); the core works without them.

1. Prep and look

bash $S/scripts/prep.sh <IMG_xxxx.MOV> $P
ffmpeg -v error -i $P/assets/talk.mp4 -vf "fps=1/10,scale=216:384,tile=6x3" -frames:v 1 -update 1 $P/build/sheet.jpg

Look at the sheet. Check that it is the right person (show the frames and confirm with the user when there is any doubt). Note where the face sits (the zoom origin, default 50% 29%), where the chin is (the card band starts at y 990), and how bright the wall is.

2. Transcribe everything

python3 $S/scripts/transcribe.py $P/assets/talk.mp4 --out $P/build/words.whisper.json --lang en

The table is the take map in original seconds; * marks restart phrases ("okay, again"). Fix mangled names later in captions.fixes.

2b. Track the face

python3 $S/scripts/face_track.py $P/assets/talk.mp4 --out $P/build/face.json

Always. The build places captions, cards and reactions around the face, inside the platform's safe area.

2c. Noisy outdoor audio?

Crickets, hum, wind, traffic: bash $S/scripts/denoise.sh $P/assets/talk.mp4 $P/build/voice-clean.wav (DeepFilterNet3, capped at 20 dB; full strength makes the voice thin and watery). Use the clean track for the cut and the captions. Band-limited voice (Bluetooth mic, a call, a downloaded clip): voice_enhance.py IN OUT.wav --mode superres (ClearerVoice; does nothing on full-band phone audio). Speech islands on noisy raw audio: vad_pauses.py / autocut.py --vad (silero-vad). Both run in the audio QA venv (bash $S/scripts/setup_audioqa.sh prints its python).

3. Choose takes (references/take-selection.md)

Ask for the script if there is one. Pick the take of each sentence that is fluent and later, keep one-breath runs as one take, and cut on WORD times: a = first word - 0.10..0.15, b = last word + 0.20..0.30. When a meme will follow a line, end that take 0.6 to 1 s after the last word so the meme sound has air. Aim for 45 to 75 s.

A scripted recording with many takes: the raw-cut tools (take-selection.md, "The raw cut, step by step"): rawcut_prep.sh makes the voice files and a frame-exact proxy, islands_tx.py transcribes each speech island on its own, takes.py finds every attempt at every script sentence with its face flags, plan_cut.py turns your picks (cut.json) into frame-exact pieces with trimmed pauses, blink-safe edges and keep/cover labels, subcheck.py catches merged restarts, assemble.py --plan + voice_smooth.py --plan make the plates and the voice, qa_cut.py checks the result. On Apple silicon, transcribe with mlx-whisper (transcribe.py --backend mlx).

Audit the rough cut before building. Whisper merges restarts and false starts into one clean sentence and smears timestamps across them ("And even the… and even the thing that…"). Render the rough cut, re-transcribe THAT voice, and ask Gemini 2.5 Pro (analyze_video) for a verbatim audit: repeats, fillers, clipped words, breaths, look-aways. A long stretch of voice with few words in the transcript is a hidden retake. A throat-clear ("khm") shows up in a pitch scan as a short voiced hum with falling pitch; Gemini's sub-second timestamps are not reliable enough to cut on. Leave ~0.2 s of breath between sentences.

3b. A single clean take?

If the recording is already one good take, don't pick takes by hand: python3 $S/scripts/autocut.py $P/assets/talk.mp4 --noise -30 prints takes with the pauses removed.

4. Pick a style, plan beats (references/styles.md, references/reel-json.md)

Seven presets: clean, editorial, meme, cinematic, launch, kinetic, pop. Recipes (custom builds, not reel.json presets; each has its own README, SYSTEM.md and scripts). Follow the README end to end:

• recipes/clean-os/, Clean OS: Apple-clean word cards, wide/tight from one 4K camera, literal phone-UI scenes (date picker, lock-screen notifications, search + stalled loading bar, Photos memory), a red Figma selection box with a cursor. Call: "Clean OS". Talking heads, reflective or explanatory.
• recipes/explainer-vector/, Vector explainer: no footage; an ElevenLabs narrator; one continuous SVG world a camera travels through, a subject that draws itself, serif headlines, word-reveal captions. Call: "animated explainer", "like the tree video".
• recipes/result-podcast/, RESULT: warm podcast edit: one or two Inter Tight words with a two-tier emphasis, Caveat handwriting, navy dust cards, polaroids, a stop-motion paper stack, film-burn leaks, comic props, dissolves between lines. Call: "RESULT style". Face RESULT (its talking-head mode; faceresult.py + example-face/, README "Face RESULT"): the speaker's face as shot, paper props / polaroids / quote cards in zones beside, above or below the face measured from face.json (the build fails one that touches the face), big two-tier captions on a navy card, film grain + dust only, full-screen cards <= 2.5 s. Call: "Face RESULT", "RESULT on my face".
• recipes/whiteboard/, Whiteboard: a split screen, a white marker board on the top half and the speaker's face on the bottom half as shot; each thought drawn live in rough marker strokes with a visible marker following the stroke, Caveat handwriting, an eraser between pages, white pill captions on the seam with the spoken word swept yellow; the board goes full screen only over a look-away (board.py + example/reel.py, a generator per reel keyed to words). Call: "Whiteboard", "a marker board edit". Read its SYSTEM.md first.
• recipes/pov-montage/, POV montage: several first-person clips cut into a story with an edit list (speed-ups, freezes), the editorial motion layer, a freeze-frame moment with a meme. Call: "cut these POV clips".
• recipes/seoul-list/, Seoul list (a format, not a footage source: the footage the user hands over first, then their library, then stock or AI full screen; one world conformed to the main footage as shot, no posed stock models, the people rules): a voice-over list of observations over 1.4 s B-roll shots (no talking head); one big word per line in Playfair Display Italic (mood, places) or Inter Tight 800 (facts) with a subline, white word flashes, white collage pages (shot shrinks into a card, red glitch word, photo card, Fluent stickers), triptychs, an Instagram comment card, a macOS frosted window swapping cut-outs, blue highlight words, an iMessage outro. Built from list.json + proxies + the VO (build.mjs). Call: "Seoul list", "a list reel over B-roll". Read its SYSTEM.md first.
• recipes/stan-style/, stan style (NEEDS real screen recordings of the tool; without them say so and propose Clean OS or RESULT): a seated talking-head tool tutorial on the core pipeline (reel.json beats from scripts/lib/stan.mjs): panel (a screen recording in the top band, behind the speaker's BiRefNet cut-out; the speaker moves down only as far as their eyes need, once per run of panels), chest captions (small lowercase phrases at 68 % that cut on their first word; single words in the hook and the diagram, forehead words near the end), a hook card (icon rows + black-on-white strip title), one white diagram with drawn-on lines entered by a zoom-blur, step and cta labels under the chin, aside. Call: "stan style", "tool tutorial". Read its SYSTEM.md first.
• recipes/kinetic-doc/, Kinetic doc: black-and-white archive documentary with one red accent: words pop on as spoken in one centred line (a big heavy word + small words), pictures arrive as prints, windows and polaroids, punch lines get their own page; works for a talking head, a voice-over with visuals and B-roll only. Not the kinetic preset. Call: "kinetic doc". Read its SYSTEM.md first.
• recipes/step-deck/, Step Deck: a tips reel as a numbered deck over a talking head: every word lands on its onset behind the speaker's head, the picture switches every 1-2 s between the face and flat word cards, paper prints and line drawings, and each step opens on a card whose giant italic numeral shrinks into place; from @ant.lon. Call: "Step Deck", "steps reel". Read its SYSTEM.md first.
• recipes/product-page/, Product page: a review or demo of a named tool, app or book laid out like a product page: white pages with the real picture, rebuilt UI and hairline drawings that a virtual camera moves through on the spoken words, the speaker's cut-out over a rounded footage card, two-tier headlines (heavy sans + italic serif), one spoken word at a time in a grey pill; from @adrien.ninet. Call: "Product page", "tool review page". Read its SYSTEM.md first.
• recipes/tactile-paper/, Tactile paper: the talk told on printed paper that moves like stop-motion (8 fps): newspaper and archive sheets that unfurl and turn with a real page fold on a maroon ground, white arrows and a crimson marker, black pill captions, the paper turning away like a page to reveal the speaker's face; from @chrismoran__. Call: "Tactile paper", "paper page turn". Read its SYSTEM.md first.
• recipes/caption-news/, Caption News: big chunked captions slammed on the spoken words with one keyword on a yellow block, a title sting that becomes the channel bug, a source tag and a highlighted document beat when the speaker names a source, the face as shot; ported from lemo-opuscar (MIT). Call: "Caption News", "news captions". Read its SYSTEM.md first.
• recipes/news-package/, News Package: the speaker is the anchor of a one-story TV segment: a sting that flies into the corner as the bug, a chest strap with a category tab, a split-flap board, schematic cards and a rundown of the points ticked off at the end; ported from lemo-opuscar (MIT). Call: "News Package", "news segment". Read its SYSTEM.md first.
• recipes/telestrator/, Telestrator: the footage freezes on the key word and gets drawn on like a sports replay (rings, marker arrows, zones, a rewind), always below or around the face, never on it; ported from lemo-opuscar (MIT). Call: "Telestrator", "sports breakdown", "freeze and draw". Read its SYSTEM.md first.
• recipes/halftone-dossier/, Halftone Dossier: the story as a retro print case file: halftone pages in four flat inks, heavy misregistered headlines, stamps that slam, a profile card, the speaker's face as shot between pages; ported from lemo-opuscar (MIT). Call: "Halftone Dossier", "case file", "dossier". Read its SYSTEM.md first.
• recipes/swiss-grid/, Swiss Grid: International Typographic Style around the speaker's face: a 6-column grid, one typeface, one red, key words laid out like a poster, a counter, exact quiet motion; ported from lemo-opuscar (MIT). Call: "Swiss Grid", "swiss poster". Read its SYSTEM.md first.
• recipes/data-story/, Data Story: when a line carries a quantity a chart draws itself on cream paper with a red-blue pencil and handwritten notes; only real numbers, each with its source on screen; ported from lemo-opuscar (MIT). Call: "Data Story", "pencil charts". Read its SYSTEM.md first.
• recipes/hologram-hud/, Hologram HUD: the thing the speaker talks about is scanned into a glowing wireframe, target boxes lock onto its parts and values roll in, cut against the face as shot, never over it; ported from lemo-opuscar (MIT). Call: "Hologram HUD", "hologram scan". Read its SYSTEM.md first. The visual inventory of every style (playing loops, soundboard, rules) is docs/PLAYBOOK.md. Check the style's prerequisite before planning (references/broll.md section 6): stan style needs real screen recordings, cinematic needs one consistent world of footage. If it is missing, say what is missing and propose another style; never fill the gap with stock. Seoul list has no footage prerequisite: it is a format (its README "Footage"). Ask the user which one (show examples/gallery/ or the showcase video) or pick by the speaker's energy. Start from examples/gallery/<style>.reel.json. To match a reference edit: python3 $S/scripts/reference_study.py <their-edit.mp4> --out <dir> [--raw <raw>] writes a 1 fps contact sheet, full-res frames every 2 s and Gemini 2.5 Pro's second-by-second edit log with a mapping onto our beats. Treat the log as a draft: verify type, sizes and framing against the frames. Then map every scene to a word time. Start from the closest file in examples/. Walk the transcript sentence by sentence. For each one, ask what the speaker just made the viewer imagine, and show it on the word. Leave some sentences bare; silence in the band makes the next card land. B-roll (references/broll.md; broll_qa.py fails the render past these):
• Hard rules (references/broll.md section 0):
  • The B-roll people rules in people-rules.json (empty by default; the user sets what their channel needs, e.g. exclude women, children or symbols; people-rules.example.json). insert_prep.py refuses a shot that breaks one, broll_vision.py picks shows the user every shot before the render (WAIT for their yes), and broll_qa.py fails the render (people). Ask the user once whether they have rules; never invent any.
  • The speaker's face keeps its as-shot colour: never a house grade or filter on the plate. Inserts are conformed to it.
  • Fewer B-rolls (talking heads <= 3 a minute), and each one shows the line it sits on (match). Stock images in a frame, card or collage are welcome and beat several video cutaways.
• Sources in order:
  1. The user's own footage, found by own_footage.py in their Photos library and footage folders and face-checked so only they appear. Before the render, show them own_footage.py sheet and wait for their yes.
  2. Stills in one frame language: AI stills or stock images (polaroid, card, collage page).
  3. Stock video last, and only inside a frame (polaroid, phone, card): never full screen when anything else fits, never for a list. broll_qa.py fails full-screen stock. Exception: B-roll-led formats (Seoul list, POV montage) are full-screen B-roll by design. There stock or AI may fill the screen, but one graded world, no posed stock models, the reference pace and 1080p are checked instead.
• One fixed house look per style (recipes/<style>/house.json, the SYSTEM.md "House look" sections): type, captions, accents and insert framing stay, and the speaker's face as shot. Never a grade on the face: house_look.py apply is retired and broll_qa.py as_shot fails a regraded plate.
• New components every reel (so reels in one style don't look the same every time): phone-UI scenes, paper props, polaroid / card / collage treatments, transitions, hook and outro devices. Before planning a named-style reel run components.py plan --style <s> (what the last 7 reels used and what is free) and fill each slot with something unused; register new ones with components.py add (with a sig); components.py check / broll_qa.py components warn on a repeat; after the user's yes components.py record.
• One character per idea. One shot per idea: a spoken list becomes typography, never three 0.5 s clips.
• Frame inserts (PiP, polaroid, split) so the face stays on screen; full screen is for the turn.
• Talking heads: full-screen B-roll <= 25 %, the speaker's face on screen >= 65 %, <= 3 inserts per minute.
• Every insert goes through insert_prep.py --ref <plate as shot> --line "<the words under it>", which refuses a shot that breaks the people rules or doesn't show the line, and grades the insert onto the speaker's plate.
• Small glances stay on screen. Cover only real look-aways (> 0.5 s or > 12 deg; cover_windows.py labels them), cheapest first: trim, tight-crop punch, hold the current graphic, framed insert, full-screen stock last. Memes: 1 to 3 per minute, on punchlines, from the library:

python3 $S/scripts/meme_find.py "the line with the punchline"
python3 $S/scripts/meme_find.py --list

If the library has nothing that fits, say so and offer to add one (step 9). Don't force a meme.

Read the taste first: python3 $S/scripts/taste.py prompt --style <style> lists every correction the user has made across reels ("you said") and the rules the skill learned ("skill rule"). The build fills its defaults and warns on the rest; plan with them.

v0.3 building blocks (all in references/reel-json.md; restraint still rules: one or two per minute each):

• Caption templates: captions.style = hype, explosive, line-focus, neo-minimal, karaoke-fill, highlighter (one keyword per phrase: heuristic, keywords, or ai: true).
• Kinetic type: textfx beats hook (the first 1.5-3 s), drum (lists, "round and round"), scramble, flipstack, headline (+ swap for "not X -> Y"), spring (section titles). Give each a to; the build warns on a short reading hold.
• Shader backgrounds on any scene (bg: {"look": "ink-warp"}), the word scene, look.shader film-grain/halftone overlays.
• Emoji beats pop an animated Fluent emoji when the glyph or name is in library/emoji (size <= 280).
• transitions at take changes (transitions.py reel $P; hard cuts stay the default, at most 2 punchy ones per reel).
• look.film film stocks baked into the plate (film_look.py apply ... --look vision3_500t; check one still first).
• matte: true + behind beats: BiRefNet cut-out, only for the behind seconds (~4-5 min per word); front: true puts the word over the speaker, through: true slides it through the head (behind on one side, in front on the other).
• cutout beats (scripts/cutout_fx.py, BiRefNet in the matte venv; references/cutout-fx.md): bg-swap (new place, light wrap
  • colour match), bg-blur (portrait mode), selective colour, spotlight, sticker (die-cut freeze that pops and wiggles), neon outline, clones (three time-offset copies), pop (head breaks out of a phone frame). One alpha pass per beat, cached; lite@1024 by default (~0.53 s/frame on the M3 Air, ~1 min per 2.5 s beat; portrait@1024 is ~4x slower for the same look at reel size). Inside ONE take; the window is frame-exact against the take and eases back into it. Reel-wide: look.cutout. Covers: cover -> build/cover-9x16.jpg + cover-16x9.jpg on the approval sheet. At most 2 cutout beats per reel.

5. Build

node $S/scripts/build.mjs $P

Read its output: the edit timeline (a missing word means a cut inside it), the caption text, the SFX table (time, sound, role, volume, why) and the WARNINGS. Fix every warning in reel.json or explain why it stays.

6. The approval gate (before the slow render)

python3 $S/scripts/approval_sheet.py $P [--upstream <cut list of a pre-cut source>] --open

It rebuilds, lints (0 errors required; sub-composition/track-density warnings are fine), runs the taste checks and snapshots the first frame, 1.5 s, just after every visible cut, each beat as it lands and fully built, and the end, into one page (build/approval.html: contact sheet, timeline, takes, beats, captions, SFX, warnings). Look at it yourself first and fix what is wrong (cards on the chin, text wrapping, a meme clipped by the edge, captions colliding with a card, a wrong person). Then send the user the page and WAIT: they flag frames and paste a change list, or approve. After their yes: approval_sheet.py $P --mark-approved. For a quick look without the page: $S/scripts/hf.sh lint and $S/scripts/hf.sh snapshot --at <edit seconds> (edit seconds = the take's edit start + (original t - take a)).

7. Previews, final render, QA (at most 3 fix rounds)

The user sees low-quality previews before anything renders at full quality. finals.py takes one or more project folders, or a batch manifest (--batch reels.json; the format is in its docstring). Run it as a tracked background job (a HyperFrames render cancels itself when its parent shell exits).

F="python3 $S/scripts/finals.py"; R="--out $P/finals --code R12 --style 'Clean OS' --title 'Short English title'"
$F preview $P $R    # -> "R12 - Clean OS (preview).mp4" (720x1280, ~4.5 Mbit/s). Send it; WAIT for the user's OK
$F render  $P $R    # delivery master -> "R12 - Clean OS.mp4": Instagram H.264 (1080x1920, 30 fps, High@4.2, BT.709,
                    # CRF 16 capped at 20 Mbit/s, AAC 256k); refuses a reel whose preview is missing or older than index.html
$F qa      $P $R    # render_report.py + broll_qa.py -> "<name>.qa.json/.html", one summary line per reel
python3 $S/scripts/qa.py $P build/reel.mp4              # SFX stem levels, A/V lengths, matte, transitions, shader flicker

The user's changes after the previews go back into the build, then new previews. The HyperFrames version is pinned in ONE place, scripts/HF_VERSION: every script (finals.py, approval_sheet.py, qa.py, snap.py, build.mjs) and $S/scripts/hf.sh read it, so every machine renders with the same version. Never call npx hyperframes unpinned. To try a new release: HF_VERSION=0.8.x $S/scripts/hf.sh ... on one reel per recipe, compare, then change the file (doctor.sh warns while the variable is set). render_report.py also works on custom builds with no reel.json (a recipe's generator wrote index.html): it checks the render against the composition and skips the checks that need reel.json (take mapping, caption layout, SFX table). The report checks streams, duration, A/V alignment, loudness, black frames, a frozen speaker, silences inside the speech (mapped to the take), caption safe area, the first 1.5 s and the SFX levels, each failure with a fix. It also runs broll_qa.py (the B-roll and motion checks). Run that on its own for custom builds without reel.json: python3 $S/scripts/broll_qa.py build/reel.mp4 --project $P [--profile talking-head|broll-led|graphics].

• budgets: full-screen B-roll, face on screen, inserts per minute;
• insert grade vs the plate;
• graphic scenes: length and motion;
• captions: >= 48 px and >= 3:1 contrast, via OCR;
• nothing over a face;
• frozen frames, HDR output, plate keyframes. PASS: deliver and mention the warnings. FAIL in round 1 or 2: apply the "agent can apply" fixes to reel.json (never gain on the mix, never hand-tuned data-volume), rebuild, lint, snapshot the changed times, re-render, report again. FAIL in round 3: stop and send the user render-report.html. A visual change they have not seen goes back through the approval sheet first.

QA renders an SFX-only stem and prints each hit's peak against the voice and its role target. Targets: ui ≈ -14, whoosh -12, impact -8, meme -3 dB vs voice p95 peak; flags anything louder than the voice or inaudible. It also checks loudness (-16 ±1.5 LUFS, TP ≤ -0.5), silences > 0.8 s inside the speech, and writes build/contact.jpg. It never adds gain.

8. Deliver

CONTENT=<the user's library of finished videos, with a NOT POSTED/ folder> $F deliver $P $R [--collection "Trial reels"] [--dry]

Loudness to -14 LUFS / -1.5 dBTP (two passes, the video is copied), then the file goes to $CONTENT/NOT POSTED/ (with --collection: one folder per video, one file per style), with a _moves.tsv line, a TRACKER row per video when the library has a TRACKER.csv, and a rebuilt TRACKER.html when TRACKER_WORK has a make_html.py. Without a library, hand over the finals.py render file. A hard QA fail (format, A/V, black or stalled picture, the people rules, the speaker's face regraded, a face covered, HDR) holds the reel until someone has looked: --allow "<name>" once it is judged fine. Handover: the takes chosen (original seconds and why), the beats and memes in plain words, the SFX count per minute, anything QA flagged, and the obvious follow-ups (music from the platform's library at post time, a different meme, the URL for the end card). Then python3 $S/scripts/taste.py log-reel $P --verdict shipped; if the user loved the look, offer python3 $S/scripts/save_style.py $P <name> --best-for "...".

9. Library work

python3 $S/scripts/trends.py                 # what's new on imgflip / Know Your Meme, what we lack
python3 $S/scripts/meme_add.py <id> <url|file> --tags ... --use ... --triggers ... --trend hot
python3 $S/scripts/sfx_fetch.py --only <id> --force   # after editing KIT in sfx_fetch.py
python3 $S/scripts/cc0_pack.py list            # the CC0 meme-sound pack (ships in the repo); build re-downloads it
python3 $S/scripts/audition.py --open         # soundboard + meme wall for a human listen

Always look at a new meme's preview.png before using it. Sounds with a review flag in the manifest have not been confirmed by ear. references/sound-and-memes.md has the mixing reasoning, sources, licences and the dead ends not to retry. Animated emoji: python3 -I $S/scripts/emoji_fetch.py (library/emoji, Fluent, MIT).

10. Every correction is taste

When the user corrects an edit decision ("too many zooms", "that sound is cheesy"), fix the reel AND record it in their words: python3 $S/scripts/taste.py add "<what they said>" [--metric punch_ins --max 2 | --set captions.size=50 | --ban-sfx riser-1] --reel <project>. Only the user's own feedback is from: user (quoted "you said"); a rule you learned yourself is --from skill. taste.py list, forget <id>, restore <id>, tag <id> user|skill. Taste is a prior: reel.json always wins.

Rules that came from getting it wrong

• B-roll is the user's world, framed and graded, or nothing (an audit of 29 reels; references/broll.md). Reels went wrong in these ways:

  • forced covers on every glance (one reel: 31 windows, speaker on screen 33 %);
  • full-screen stock strangers 15-44 b* colder than the plate;
  • one 0.5 s clip per noun;
  • static graphic scenes;
  • small, low-contrast captions on a light hoodie;
  • panels opening over the speaker's face;
  • stan without screen recordings, and a Seoul list filled with unrelated posed stock models in three light worlds. The UI animation was fine; what went on screen, and how often, was not.

• One reel at a time through approval_sheet.py; never batch-render a wave of styles without a sheet per reel (7 styles rendered from one template in 7 minutes came out with 0-2 approval files). Custom builds with no reel.json have no approval sheet: there the user's OK on the finals.py preview copies is the gate, and nothing renders at delivery quality before it.

• The speaker's plate must cover the whole reel: a talking-head clip that ends at the voice's length leaves the reel's tail (music fade, 0.3-0.5 s) black, which flashes at Instagram's loop point. Give the plate a held last frame (tpad=stop_mode=clone) and run it to the end; check the last 0.4 s of every render.

• Run hyperframes render as a tracked background job, never nohup ... & from a tool shell: when the parent shell exits the render cancels itself (render_cancelled_parent_exited). Masters with animated grain can come out as 10-bit HEVC at ~50 Mbit/s: finals.py render re-encodes every master to H.264 8-bit (CRF 16, capped at 20 Mbit/s).

• A style is a SYSTEM, not a template. When breaking down a reference, write the invariants (what makes it the style), the house look (house.json: what stays fixed reel to reel), the content slots (what follows the script), a generator per slot, and a catalog of used components (catalog.json, read and written by scripts/components.py; see recipes/clean-os/SYSTEM.md section 5).

  • The default is one fixed house look per style, with small variation per reel.
  • Pasting the previous reel's scenes where the script doesn't call for them still reads as "the same edit".
  • Reusing the house's look is the point.

• Transcribe the whole recording; choose takes from the table, never by scrubbing.

• Cut on word times, never whisper segment times.

• Snap zooms, not crossfades, between takes of the same sentence.

• Voice loudness is fixed in prep, before SFX. Never lift the finished mix.

• SFX level is relative to this voice (build measures it). Never hand-tune data-volume.

• A meme sound never sits on top of a word. Give it a pause.

• No meme sound twice in one reel. Meme sounds: 1 to 3 per minute.

• One card in the band and one thing in the reaction slot at a time.

• No em dashes in on-screen text.

• Meme sounds and green-screen clips from the internet are usually other people's media: the user adds them at their own risk (fine for many IG and TikTok reactions, not for YouTube Content ID). Say so if the user mentions YouTube.

• Shoot or prefer 4K: one camera gives a wide and a tight shot with no upscaling. No 720p B-roll; on Mixkit only clips offered in 2160p carry the free commercial licence. Your own unused frames are often the best B-roll.

• HyperFrames: anything tweened more than once gets fromTo with explicit values (a bare to() locks a stale start value depending on the renderer's seek order). Grow SVG shapes with attr, not scale transforms. Every <video> needs an id. Lint, then snapshot every beat and look at it, before every render.

• Light accent colours (lime, yellow) need dark text on pills and tags: brand.onAccent.

• Music ducks under every spoken line (music.duck); under a freeze it nearly disappears. The QA SFX stem excludes the bed.

• Calibration (6 top reels): 113 of 119 transitions are hard cuts, median shot ~3 s, audible SFX 0.4-0.9 per 10 s on graphics (not on cuts), B-roll 20-35 % of runtime. Default to restraint.

• Hide jump cuts with short dissolves (0.2 s) or a shot-size change, not a zoom on every cut; the user found per-cut zooms annoying (at most three comic punch-ins per reel). Before cutting, build an attempt log of the WHOLE raw take with Gemini 2.5 Pro.

• Hide each caption with an explicit fromTo placed after its fade-in; a bare set inside the fade gets overridden.

• The person matte rebuilds itself when talk.mp4 or the behind beats change (signature in assets/talk-matte.json). On the u2net fallback (no matte venv), delete assets/talk-matte.webm after a re-cut or old cut-outs float over the new footage.

• Cutting picture and voice separately (Clean OS, POV montage): snap every segment to the frame grid and cut both at the same snapped times; otherwise each piece rounds to whole frames and the voice drifts early (43-54 ms by the end of a 23-piece cut). qa.py --av-only checks lengths; tests/test_assemble_sync.py is the regression test.

• HyperFrames clip times for footage (takes, holds, matte, transition and cutout windows) are frame counts / fps TRUNCATED to 6 decimals (fgrid in build.mjs), never rounded: the renderer snaps a start only within 0.001 frame and samples a video at floor((t - start) x fps), so 0.067 for 2/30 shows the clip a frame late and 0.066667 repeats its first frame. An ffmpeg window cut to match (cutout_fx.py) takes -ss as the exact frame time to 6 decimals and -t half a frame short.

• Per-letter or per-shader motion is a pure function of the timeline time (painters, the hf-seek event), never rAF or a chain of tweens. Animated emoji are WebM <video>, never APNG <img> (APNG animates on the wall clock).

• APIs: ElevenLabs through the direct key in .env (the MCP connector's grant budget runs out); Gemini 2.5 Pro for long video (Flash truncates), key checked with one call first; yt-dlp >= 2026.08.19 for YouTube; never pass Instagram cookies.

Files

• scripts/prep.sh transcode + voice loudnorm
• scripts/transcribe.py whisper (PATH, or --backend mlx on Apple silicon) → words json + take table; decodes without conditioning on earlier text, so retakes stay separate
• scripts/build.mjs reel.json → HyperFrames index.html, SFX mixing and rules
• scripts/qa.py render QA with SFX stem level check, A/V lengths (--av-only), matte, transitions, shader flicker
• scripts/broll_qa.py B-roll and motion QA (budgets, grade, graphics motion, captions via ocr_text.js / macOS Vision, faces covered, stock inside a frame, own footage only the speaker, no posed stock models, people rules and line match (broll_vision.py, Gemini), the speaker's face as shot, 1080p sources, one world and shot pace for B-roll-led styles, freezes, HDR, keyframes); scripts/broll_vision.py the people / line check and the pick sheet; scripts/own_footage.py the user's own footage (index + Gemini tags, face check, confirmation sheet; library/me/ stays local); people-rules.json the configurable B-roll people rules (empty by default; people-rules.example.json); recipes/<style>/house.json the fixed house look per style (scripts/house_look.py measures; never applied to the face); scripts/insert_prep.py + scripts/grade_lib.py insert cut + SDR + fps + grade conform; scripts/cover_windows.py / plan_cut.py keep-or-cover verdict per off-lens window; references/broll.md
• scripts/sfx_fetch.py build/refresh the SFX kit (Mixkit), normalized, manifest
• scripts/meme_add.py add a meme clip/still (key, crop, alpha WebM, preview)
• scripts/meme_find.py shortlist memes and meme sounds for a line
• scripts/trends.py trending meme names not yet in the library
• scripts/audition.py HTML soundboard + meme wall
• scripts/doctor.sh checks tools, key and library, with fixes
• scripts/reference_study.py reverse-engineer a reference edit (sheet, frames, Gemini edit log)
• references/reference-study-prompt.md the edit-log prompt (improve it here)
• examples/ real reel.json files from shipped reels (English): one per preset in examples/gallery/, two motion edits
• README.md install, agent setup (Claude Code / Codex / any agent), quick start
• scripts/lib/motion.mjs scenes (card, stats, fly3d, image, sentence), scene transitions, editorial captions, music bed
• scripts/autocut.py pause-trimmed takes for a single clean take
• scripts/broll_gen.py AI still B-roll with Gemini (9:16), needs GEMINI_API_KEY
• scripts/tts_elevenlabs.py narrator voiceover with word timings (ElevenLabs, takes by seed)
• scripts/denoise.sh DeepFilterNet3 speech denoise, capped at 20 dB (sets up its own py3.11 venv)
• recipes/<name>/ named styles beyond the presets (README + SYSTEM.md + scripts; an English worked example in a recipe's example/ where it has one; Face RESULT's is recipes/result-podcast/example-face/; the lemo-opuscar ports carry their MIT licence and CREDITS.txt)
• docs/PLAYBOOK.md every style, toolkit and rule in one place (the shareable inventory)
• library/music/ licensed music beds + manifest
• library/sfx/ kit + manifest.json; library/memes/<id>/ clips + meta.json
• templates/fonts/ Geist, Inter, Inter Tight, Playfair Display, Montserrat, Oswald, Unbounded, JetBrains Mono, Caveat (OFL, latin + cyrillic woff2)
• scripts/lib/facereel.py the shared base of the custom talking-head builders (Face RESULT recipes/result-podcast/faceresult.py, Whiteboard recipes/whiteboard/board.py, Clean OS recipes/clean-os/cleanos.py + its parts kit.py; --api prints each one's calls): plate as shot + held tail, word refs, GSAP timeline, SFX by role, ducked bed, face zones and the face guard, the talking-head budgets, build/{beats,plan,sfx_events}.json
• references/reel-json.md the spec and beat types
• references/take-selection.md choosing takes (adapted from mariagorskikh/talking-head-reel, MIT)
• references/sound-and-memes.md mixing, sources, licences, dead ends
• scripts/lib/caption-templates.mjs (+ metrics.json, ai-tag.mjs) six caption templates; scripts/font_metrics.py regenerates the metrics
• scripts/lib/stan.mjs stan style blocks (panel, hook, diagram, step, cta, aside) and the chest captions
• scripts/lib/kinetic.mjs textfx blocks; scripts/lib/shader-layer.mjs + templates/vendor/hf-paper.js shader looks; scripts/lib/emoji-pop.mjs + scripts/emoji_fetch.py Fluent emoji
• scripts/transitions.py, scripts/film_look.py, scripts/gen_luts.py transitions and film stocks (LUTs in library/luts)
• scripts/matte.py BiRefNet person matte; scripts/vad_pauses.py, scripts/voice_enhance.py audio QA
• scripts/cutout_fx.py BiRefNet effects (cutout beats, look.cutout, covers, model demos on stills); references/cutout-fx.md; tests/test_cutout_fx.py (fake model, no GPU: every effect, the frame grid, release); tests/test_decode_levels.py (RGB decode matches the BT.709 spec, a decode -> Writer round trip keeps the levels)
• scripts/approval_sheet.py, scripts/render_report.py, scripts/taste.py (+ lib/taste.mjs, taste.json), scripts/save_style.py workflow
• scripts/finals.py previews -> final render -> QA -> delivery into the user's library of finished videos, per reel or a batch
• scripts/allframes_qa.py RENDER.mp4 --fps 24 --rules people one Gemini Flash call on every frame of a finished reel (~7 cents): the people rules anywhere on screen, not only in declared B-roll layers (a warning, never a pass: recall ~8/10, times ~1 s)
• templates/briefs/build-one-reel.txt / finish-one-reel.txt the two hand-offs of one reel (Opus builds to the preview, Sonnet finishes after the user's OK); scripts/reel_usage.py sums a reel's helper transcripts (turns, tools, tokens, images)
• scripts/broll_fetch.py stock B-roll originals (Pexels by link, Mixkit search) + manifest.json
• scripts/wikimedia_fetch.py Wikimedia Commons pictures (search, categories, licence + author in the manifest); scripts/google_images.py Google Images via Apify; scripts/image_sources.py the shared order, EN+RU queries and size rule; scripts/image_pick.py brief -> candidates -> vision scores -> pick or flag -> contact sheet
• scripts/HF_VERSION the one HyperFrames version; scripts/hf.sh / scripts/hf_version.py call it pinned
• scripts/toolchain.py this machine's toolchain fingerprint vs another machine's (doctor.sh runs it); scripts/venvs/*.txt exact venvs
• Raw cut of a scripted multi-take recording (references/take-selection.md): scripts/rawcut_prep.sh voice wavs + frame-exact proxy, scripts/islands_tx.py per-island transcripts, scripts/takes.py every attempt per script sentence, scripts/facescan.py (--pts: true frame times) head and eyes per frame, scripts/plan_cut.py frame-exact pieces + keep/cover, scripts/subcheck.py hidden restarts, recipes/clean-os/assemble.py --plan [--alt] plates, scripts/voice_smooth.py --plan voice, scripts/qa_cut.py raw-cut QA, scripts/gem_audit.py Gemini attempt log / audit / gaze, scripts/eyestrip.py eye close-ups to check a flag
• scripts/setup_{captions,looks,matte,audioqa}.sh the optional venvs; docs/THIRD_PARTY/ sources and licences per pack