Motion performance
Open-source interaction-design intelligence for AI coding agents - securely discover, select, adapt and validate UI motion, effects and interaction patterns.
npx -y skills add Suraj787/motif --skill motion-performanceAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
Copied from the file, not written here
Use when validating that an interaction stays within performance budget, animating cheap properties, avoiding jank, and never running costly decorative motion behind dense UIs.
SKILL.md
1.3 KB, 241 tokens by cl100k_base, as published. Nobody here has run it
Motion Performance
Responsibility: Keep interactions cheap and smooth. Protect dense work UIs from decorative cost.
When to invoke
- During implementation and at validation (step 13 of the root workflow).
Inputs
- The implemented interaction, its animated properties, and the page context.
Outputs
- Pass/fail against the performance budget, with required fixes.
Checks
- Animate
transform/opacity; avoid layout-triggering properties (width, height, top/left, box-shadow spread) unless justified. - No continuous decorative motion behind dense or data-heavy screens.
- Effects are composited and do not cause long frames or layout thrash.
- Off-screen and reduced-motion paths do no needless work.
- WebGL/canvas only when a simpler technique cannot meet the objective.
How it connects
- Reads
intelligence/performance guidance andregistry/cost metadata. - Reports to
implementation-validation; failures block the ship.
Notes
If an effect is expensive and the objective could be met more cheaply, send it back to
effect-selection. Performance is a selection input, not just a post-hoc check.
Gives 0 of the 12 instructions most performance cost skills give in 241 tokens
Counted across 803 of the 1,058 authors here whose files we hold, read 2026-08-06
- keep skill files under 500 linesin 82 of 803, across 17 files
- use imperative form in instructionsin 81 of 803, across 10 files
- draft assertions while test runs are in progressin 75 of 803, across 9 files
- create two to three realistic test promptsin 74 of 803, across 8 files
- write skill descriptions to be pushyin 72 of 803, across 7 files
- save test cases to evals jsonin 72 of 803, across 6 files
- ask questions about edge cases and input formatsin 71 of 803, across 6 files
- save timing data immediately when runs completein 70 of 803, across 5 files
- include all trigger conditions in the skill descriptionin 69 of 803, across 3 files
- launch all test runs in a single turnin 69 of 803, across 3 files
- capture intent before writing a skillin 67 of 803, across 1 file
- import directly instead of barrel filesin 52 of 803, across 15 files
Said here and by no other author read
- avoid layout-triggering properties
- forbid continuous decorative motion behind dense screens
- composite effects to prevent layout thrash
- ensure off-screen paths do no needless work
- use simpler techniques before WebGL or canvas
- report pass or fail against the performance budget
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.