Effect selection
Use when you have multiple candidate effects and must rank them transparently and select the simplest one that fully achieves the interaction objective.From its SKILL.md
npx -y skills add Suraj787/motif --skill effect-selectionAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Effect Selection
Responsibility: Rank candidates transparently and choose the simplest fully effective approach. Novelty must never outrank usability.
When to invoke
- After
effect-discovery(steps 9-10 of the root workflow).
Inputs
- The candidate set from
effect-discovery. - The interaction objective and constraints.
Outputs
- A transparent ranking table with explicit criteria and scores.
- The selected effect with a written justification for why it is the simplest effective choice.
- A rejected-alternatives note for the decision log.
Ranking criteria
- Effectiveness against the objective.
- Complexity / implementation cost (lower wins on ties).
- Accessibility and reduced-motion friendliness.
- Performance cost (transform/opacity preferred).
- Dependency footprint and licence cost.
- Design-system fit.
- Appropriateness to website vs web application.
How it connects
- Uses
python -m motifranking to keep scoring reproducible and auditable. - Passes the winner to
framework-adaptation; logs the table viasource-governance.
Notes
When two candidates tie on effectiveness, the simpler, cheaper, more accessible one wins. Combining multiple high-attention effects requires explicit justification recorded here.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.