Analyze
Analyze a screen recording of an animation to characterize its motion — timing, easing, transforms, and sequencing — so it can be recreated as web code. Use when the user drops or points at a video of an animation (.mp4/.mov/.webm/.mkv/.m4v/.avi/.gif) and says things like "I want this animation on my site", "recreate this motion", "how is this animated", or runs /motiscope:analyze.From its SKILL.md
npx -y skills add KumarSashank/motiscope --skill analyzeAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
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motiscope: analyze
Turn a screen recording of an animation into a precise, target-agnostic animation spec you can hand to /motiscope:recreate. A bundled Python pipeline measures the motion (a dense per-frame motion-energy curve + ffmpeg signal analysis — this is the source of truth for timing and easing) and extracts a small set of curated PNG keyframes for you to see. You combine the two into the spec.
Resolve the scripts directory (do this first)
Every command below runs a bundled script. Set SCRIPTS:
SCRIPTS="${CLAUDE_PLUGIN_ROOT:-}/scripts"
# Fallback for harnesses that don't export CLAUDE_PLUGIN_ROOT: this SKILL.md lives at
# <plugin>/skills/analyze/SKILL.md, so scripts are two levels up. Use the absolute
# path of the directory containing the SKILL.md you just Read.
if [ ! -f "$SCRIPTS/ingest.py" ]; then
SCRIPTS="<absolute dir of this SKILL.md>/../../scripts"
fi
if [ ! -f "$SCRIPTS/ingest.py" ]; then
echo "ERROR: cannot find ingest.py — check the plugin install." >&2; exit 1
fi
On Windows use python instead of python3 in every command below.
Step 0 — preflight (silent on success)
python3 "$SCRIPTS/mvsetup.py" --check
Exit 0 → proceed silently. Non-zero → ffmpeg/ffprobe are missing; hand off to /motiscope:doctor (don't try to analyze without them).
Step 1 — resolve the input video
- If the user gave a path (in
$1or their message), use it. - Otherwise scan the drop folder and project root:
ls -t animations/*.{mp4,mov,webm,mkv,m4v,avi,gif} *.{mp4,mov,webm,mkv,m4v,avi,gif} 2>/dev/null | head- Several candidates → ask the user (
AskUserQuestion) which one. - Exactly one → use it.
- None → tell the user to drop a recording into
animations/(or pass a path) and stop.
- Several candidates → ask the user (
Local files only. motiscope does not download URLs. If the user pastes a URL, ask them to screen-record it and drop the file in.
Step 2 — run the pipeline
python3 "$SCRIPTS/ingest.py" "<video>" --preset balanced
It writes to .motiscope/<slug>/ and prints a summary, the report.md path, and the ordered curated frame list.
Choose a preset (this is the main token dial)
The number of frames you Read is what costs tokens (~300–400 tokens/frame); the numeric analysis is free. Frame count tracks motion complexity, capped by the preset — it does not grow with video length.
| Preset | Frame cap | Resolution | Use when |
|---|---|---|---|
--preset draft | 12 | 512px | quick look, tight token budget |
--preset balanced (default) | 32 (usually lands 8–20 after dedup) | 640px | most cases |
--preset detailed | 48 | 960px | dense multi-beat sequences, or reading on-screen text |
--preset landing | 44 | 1280px | web/landing walkthroughs — cover each section's design at readable resolution + its in-section motion |
Start with balanced. Only reach for detailed if the animation is intricate or you couldn't read a label; use draft for a fast first pass. If the user hasn't said, pick balanced and mention they can ask for more detail.
Focus a section of a longer video (--start / --end)
For anything longer than ~15s, or when the user points at a specific moment ("the part around 0:12", "the last second"), analyze just that window instead of a sparse whole-clip scan. Times accept SS, MM:SS, or HH:MM:SS; frame/segment timestamps come back in absolute source time.
python3 "$SCRIPTS/ingest.py" "<video>" --preset detailed --start 0:12 --end 0:15
Capture fast content densely (--fps)
Within a (short) focus window you can force a uniform sample rate so nothing between keyposes is missed — e.g. --fps 20 gives up to a frame every ~50ms. Near-identical frames are still collapsed unless you pass --no-dedup. Combine with a short window so the budget isn't blown:
python3 "$SCRIPTS/ingest.py" "<video>" --start 1.0 --end 3.0 --fps 20 --frame-budget 48
Complex / long animations: auto-decompose
For clips ≥8s with two or more motion beats, ingest.py auto-decomposes by default: it finds the beats, then concentrates frames on each motion segment (drilling densely) and gives each hold just one representative frame — so the budget is spent on motion, not dead air. A 10s clip with a 5s hold in the middle spends ~0 frames on the hold. The report notes when this happened.
Control it with --decompose (force on) / --no-decompose (force the flat single-pass). Auto is the right default; force it off only if you specifically want even coverage across the whole timeline.
Other flags: --frame-budget N / --resolution W override the preset; --format jpg for gradient-heavy recordings that bloat as PNG; --no-dedup to keep every sampled frame; --out DIR (default .motiscope/).
Small elements register now. The primary motion signal is localized (built from the most-active regions of the frame), so a small button/card/icon moving on a large page reads as real motion instead of washing out. The stagger direction in the report tells you the sequencing (e.g.
left-to-right, ~200ms each) — use it when building the spec'sstagger.
Step 3 — read the analysis, then the frames
The division of labor is the whole point:
- The numbers give you the WHEN.
report.mdmeasured the timing you can't see in a still: exact durations, the per-segment easing curve (a real cubic-bezier fitted from the velocity profile), the beat/segment boundaries, the stagger timing (~ms between items), and any loop period. Trust these — a screenshot has no time axis, so this is the one thing that isn't guessable. - You give the WHAT. The frames are yours to read with full vision. Identify the elements and — crucially — what kind of animation each one is. motiscope does not classify animation types, and you are not limited to fade/slide/scale: name whatever you actually see — a mask reveal, a path/line draw, a morph, a rotate/skew, a 3D flip, a text split/typewriter, a blur, a color shift, a parallax, a physics/spring bounce, particles, a clip-path wipe, anything. The pipeline deliberately leaves this to your perception because you're better at it than any hand-coded classifier.
Steps:
Readthe printedreport.mdfor the measured timing (energy sparkline, segment/beat table with the fittedcubic-bezier, stagger timing, loop).Readevery curated frame in one message (parallel Reads) so you see them in order. Filenames encodet=<seconds>+ why each was picked, so you can line frames up against the measured timeline.
Read timing from the numbers; read everything else from the frames.
The frames are evidence, not an inventory
Frames are chosen by the motion-energy signal. Anything small, low-contrast, briefly visible, or mostly occluded barely moves that signal and may not appear in a single curated frame — while still being a headline feature of the animation. A train crossing a bridge was missed exactly this way.
Before you commit to a spec:
- Ask "is anything else moving?" and go check the clip, not just the frames. Diff a region across the whole video, or sample uniformly at a rate the curation skipped.
- If the user names something you cannot see, believe them and go look. Its absence from the frames is not evidence of its absence from the animation.
Before you trust a number
A failed automated measurement does not crash. It returns a confident float.
- Two estimators, or you have none. Measure the same quantity a second, independent way (different scale, different feature, different algorithm). Agreement is a result; a disagreement of 6× means at least one is lying, and you cannot tell which by looking.
- Say "not recoverable" when methods disagree. Averaging
-0.03 .. 0.63into0.30invents a fact. Reporting the range is the finding. - Occluded features report clamped constants. A value that is pinned at a frame edge, or that stays put while everything around it moves, is not a measurement.
- Scroll-driven ≠ time-driven. For a parallax, scroll-zoom or pinned section, the seconds in the recording are the recorder's. Only ratios (layer speed ÷ scroll speed) are intrinsic. One clip can contain both kinds of clock.
The full list, with the real failures behind each one, is in
references/measurement-traps.md. Read it before reporting any velocity, easing or ratio you
derived yourself rather than reading out of report.md.
Step 4 — produce the animation spec
Emit a target-agnostic spec: a timing skeleton (measured) + your visual reading (what each element is and does). Schema:
{
"duration_ms": 2000,
"canvas": { "w": 800, "h": 600, "bg": "#ffffff" },
"loop": false,
"scroll_driven": false,
"elements": [{ "id": "card", "role": "card" }],
"timeline": [
{ "target": "card", "start_ms": 0, "dur_ms": 400,
"ease": "ease-out", "bezier": [0.16, 1, 0.3, 1],
"animation": "fade + slide up",
"props": { "opacity": [0, 1], "y": [24, 0] },
"source": { "timing": "measured", "everything_else": "seen" } }
],
"stagger": { "children": "card", "each_ms": 80 },
"notes": "e.g. 'headline does a per-word mask reveal'; 'logo path draws in'"
}
Rules:
start_ms,dur_ms,ease,bezier, staggereach_ms, loopperiod_msare MEASURED — copy them fromreport.md/motion.jsonverbatim. Especially: use the fittedcubic-bezierdirectly (CSScubic-bezier(...), Framer[..], GSAPCustomEase) — it's the real curve, not a guess.animation,elements,props(magnitudes/direction/colors), and the animation type are YOURS from the frames — describe the actual effect in the free-textanimationfield (open vocabulary), and put your best-estimate property values inprops. Direction, scale, rotation, opacity, morph, draw, etc. all come from what you see, not from the numbers.- Be honest about a leading
hold: a gentle ease-in's slow start can read as a short hold (sub-pixel motion is invisible in the analysis thumbnails). Check the first frames — if the element already moved slightly, treat it as the start of the ease, not a delay. - Loops: if the report flags a loop, set
"loop": truewithperiod_ms. It can be a half-cycle for back-and-forth motion — decide loop-vs-yoyo from the frames. - If an effect can't be reduced to
props(a complex morph, a particle system, a shader), say so inanimation/notesand letrecreatebuild it directly from your description — don't force it into simple props. - Scroll-driven captures: set
"scroll_driven": trueand do not copyduration_msinto the spec as if it were the design's. Report ratios (layer speed ÷ page-scroll speed) and note which quantities belong to the recorder. A clip can be scroll-driven and contain a time-driven object (a train, a spinner, a looping badge) — measure that object's speed separately. - Label every number you derived yourself (a velocity, a ratio, a period) as measured, estimated, or not recoverable. Never let a chosen value read as a measured one.
Step 5 — offer to recreate
Summarize the animation in one or two sentences, then offer:
Recreate this as GSAP, CSS, Framer Motion, or Lottie/SVG? Run
/motiscope:recreate <target>.
The spec you just built is saved in .motiscope/<slug>/manifest.json; recreate will reload it (plus motion.json) if you don't hand it over directly.
Notes
- Token cost lives entirely in the frames (~24–48 PNGs). The motion curve is numbers — effectively free. If you already analyzed this clip in the session, don't re-run; reason from what you have.
- Best results come from high-fps, lightly-compressed captures. Warn the user if a recording is heavily compressed or very low frame rate.