Effect discovery
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 effect-discoveryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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Use when a pattern and interaction objective are fixed and you need to enumerate candidate effects from the approved offline registry that could realise that pattern.
SKILL.md
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Effect Discovery
Responsibility: Given a pattern + constraints, produce a set of candidate effects from the approved registry. Discovery is breadth; selection comes next.
When to invoke
- After
interaction-design(step 8 of the root workflow).
Inputs
- The chosen pattern and constraint set.
- Target framework and design-system tokens.
Outputs
- Multiple candidate effects, each with: registry id, complexity tier, dependencies, framework fit, accessibility notes, and provenance.
How it connects
- Queries
registry/viapython -m motif(offline approved registry by default). - Reads
intelligence/to map a pattern to candidate effect families. - Only
source-governancemay widen the search beyond the offline registry via an explicitsource-refresh.
Notes
Always return more than one candidate, and always include the least-complex option
(often "CSS-only" or "no motion"). Do not pre-rank here; hand the full candidate set to
effect-selection. Discard any candidate whose licence or provenance is unresolved.