The leaf PR. Replaces the placeholder SKILL.md from PR 1 with the real
5-step workflow that loads the per-topic references on demand
(skill-creator's progressive-disclosure pattern), and adds a top-level
orchestrator that runs every tier and reports a pass/fail summary.
SKILL.md changes:
- Frontmatter unchanged from PR 1 (already covers the trigger phrases
and out-of-scope cases)
- Body rewritten as a 5-step workflow:
1. Lint (load escape-hatch.md if blockers)
2. Plan (load api-map.md, then per-topic references on demand)
3. Generate (HF index.html with paused GSAP timeline)
4. Validate (render_diff.sh against per-tier threshold)
5. Document gaps (TRANSLATION_NOTES.md if needed)
- Includes a "Source contains -> Load reference" table so the agent
only loads the references the source actually needs
- Documents the validated baseline numbers (T1 0.974, T2 0.985,
T3 0.953, T4 8/8) so reviewers can reproduce
- Calls out the critical Remotion encoder config (PNG + BT.709) that
avoids the ~0.05 SSIM hit from yuvj420p vs yuv420p
Orchestrator (assets/test-corpus/run.sh):
- Iterates tier-1-* through tier-4-* directories
- T1-T3: setup -> lint -> npm install (lazy) -> render Remotion ->
render HF -> SSIM diff at the fixture's expected threshold ->
generate strip on failure
- T4: validate.sh (lint-only)
- Emits run-report.json with per-tier pass/fail and aggregate counts
- Accepts a single-tier argument for fast iteration: ./run.sh tier-1-title-card
Validated end-to-end on a clean checkout:
▶ tier-1-title-card → mean SSIM 0.9739 (≥ 0.95) ✓
▶ tier-2-multi-scene → mean SSIM 0.985292 (≥ 0.95) ✓
▶ tier-3-data-driven → mean SSIM 0.952941 (≥ 0.9) ✓
▶ tier-4-escape-hatch → 8/8 cases ✓
passed 4/4, failed 0, skipped 0
Closes the 7-PR stack: scaffold, eval harness, 4 tiers of corpus,
references, and now the SKILL.md body that ties everything together.
7.8 KiB
name, description
| name | description |
|---|---|
| remotion-to-hyperframes | Translate a Remotion (React-based) video composition into a HyperFrames HTML composition. Use when (1) the user provides Remotion source (`.tsx` files using `useCurrentFrame`, `Sequence`, `AbsoluteFill`, `interpolate`, `spring`, `staticFile`, etc.) and asks to port, convert, or migrate it to HyperFrames; (2) the user pastes a Remotion entry point (`Root.tsx`, `Composition`) and wants HTML; (3) the user links a Remotion repo and asks for the HyperFrames equivalent; (4) the user says "port my Remotion project", "translate this Remotion code", "rewrite as HTML", or "I have a Remotion comp, make it HyperFrames". Skill detects unsupported patterns (useState, useEffect with side effects, async calculateMetadata, third-party React component libraries, `@remotion/lambda` features) and recommends the runtime interop escape hatch instead of attempting a lossy translation. |
Remotion to HyperFrames
Overview
Translate Remotion (React-based) video compositions into HyperFrames (HTML + GSAP) compositions. Most Remotion idioms have direct HyperFrames equivalents — the translation is mechanical for ~80% of typical compositions. This skill encodes the mapping and guards against the lossy 20% by refusing to translate patterns that don't fit HF's seek-driven model and recommending the runtime interop pattern from PR #214 instead.
The skill ships with a tiered test corpus (T1–T4, 4 fixtures total) that grades translations against measured SSIM thresholds. Don't translate without running the eval — a translation that "looks right" but renders 0.05 SSIM lower than the validated baseline is silently wrong.
Workflow
Step 1: Lint the source
Run scripts/lint_source.py over the Remotion source directory. The lint detects patterns that can't translate cleanly:
- Blockers (refuse + recommend interop):
useState,useReducer,useEffect/useLayoutEffectwith non-empty deps, asynccalculateMetadata, third-party React UI libraries (MUI, Chakra, Mantine, antd, shadcn, Radix, NextUI). - Warnings (translate after dropping the construct):
@remotion/lambdaconfig,delayRender,useCallback,useMemo, custom hooks. - Info (translate with note):
staticFile,interpolateColors.
If any blocker fires, stop. Read references/escape-hatch.md and surface the recommendation message. Warnings don't stop translation — drop the offending construct in step 3 and note the gap in TRANSLATION_NOTES.md. @remotion/lambda config is the canonical warning case: the skill drops the import + renderMediaOnLambda(...) calls but translates the rest of the composition.
Step 2: Plan the translation
Read references/api-map.md — the index of every Remotion API and its HF equivalent or per-topic reference. Identify which topic references you'll need based on what the source uses:
| Source contains | Load reference |
|---|---|
Composition, defaultProps, schema, calculateMetadata |
parameters.md |
Sequence, Series, Loop, AbsoluteFill, Freeze |
sequencing.md |
useCurrentFrame, interpolate, spring, Easing, interpolateColors |
timing.md |
Audio, Video, Img, IFrame, staticFile, delayRender |
media.md |
TransitionSeries, @remotion/transitions |
transitions.md |
@remotion/lottie |
lottie.md |
@remotion/google-fonts/<Family>, Font.loadFont, @font-face |
fonts.md |
Don't load all of them — load only what the specific source needs.
Step 3: Generate the HF composition
Emit index.html with:
- Root
<div id="stage">carrying the composition'sdata-composition-id,data-start="0",data-duration(in seconds),data-fps,data-width,data-height, plus onedata-*per scalar prop. - A flat list of scene divs with
data-start/data-duration/data-track-index. - Inline
<style>for layout; CSS sets thefromstate of every animated property. - A single
<script>tag at the bottom containing one pausedgsap.timeline({paused: true}). Every RemotionuseCurrentFrame()derivation becomes a tween on this timeline at the right offset. window.__timelines["<composition-id>"] = tl;registers the timeline with HF's runtime.
Custom React subcomponents inline as repeated HTML using the prop interface as the template (see parameters.md for the per-instance data-* pattern).
Step 4: Validate
Run the eval harness — references/eval.md for the full guide. Quick path:
# Render Remotion baseline (after npm install in the fixture)
cd remotion-src && npx remotion render <CompositionId> out/baseline.mp4
# Render HF translation
cd ../hf-src && npx hyperframes render --output ../hf.mp4
# SSIM diff
../../scripts/render_diff.sh ./remotion-src/out/baseline.mp4 ./hf.mp4 ./diff
Threshold: ~0.02 below p05 of the source's complexity tier (see eval.md's validated thresholds table). If the diff fails, run scripts/frame_strip.sh to see which frames diverged, then re-read the relevant timing/sequencing/media reference.
Critical: both renders must use matching pixel format. Set Config.setVideoImageFormat("png") + Config.setColorSpace("bt709") in the Remotion source's remotion.config.ts — otherwise the diff measures encoder differences (~0.05 SSIM hit), not translation fidelity.
Step 5: Document gaps
Anything that didn't translate cleanly (volume ramps dropped, custom presentations approximated, fonts substituted) gets a TRANSLATION_NOTES.md written next to the HF output. See references/limitations.md for the format.
What this skill explicitly does NOT do
- Translate React state machines. Compositions that drive animation via
useState+useEffectare not deterministic frame-capture targets in HyperFrames' seek-driven model. Recommend the runtime interop pattern. - Run Remotion's render pipeline alongside HyperFrames. That's the runtime interop pattern from PR #214 — a separate solution for compositions that fail this skill's lint.
(@remotion/lambda is not a blocker — Lambda config is deployment, not animation. The skill drops it as a warning and translates the rest. See references/escape-hatch.md.)
How to grade your own translation
Run the test corpus orchestrator:
./assets/test-corpus/run.sh
It runs T1, T2, T3 (render + diff) and T4 (lint validation), prints a per-tier pass/fail table, and emits an aggregate JSON report. Use this to verify the skill is working end-to-end on a clean checkout — and as a regression check after editing any reference.
Validated baseline (as of 2026-04-27):
| Tier | Composition shape | Mean SSIM | Threshold |
|---|---|---|---|
| T1 | single-element fade-in | 0.974 | 0.95 |
| T2 | multi-scene + spring + audio + image | 0.985 | 0.95 |
| T3 | data-driven, custom subcomponents, count-up | 0.953 | 0.90 |
| T4 | escape-hatch (8 lint cases) | 8/8 pass | n/a |