skills/ravnhq/ai-toolkit/platform-frontend

platform-frontend

SKILL.md

Principles

  • Start with local state — lift only when shared
  • Organize code by feature, not by type
  • Use named exports for better refactoring and searchability
  • Never use barrel files (index.ts re-exports) — they break tree-shaking and slow builds
  • Measure before memoizing — don't optimize what isn't slow

Rules

See rules index for detailed patterns.

Examples

Positive Trigger

User: "Choose state boundaries and data-fetching patterns for this web app."

Expected behavior: Use platform-frontend guidance, follow its workflow, and return actionable output.

Non-Trigger

User: "Write a Swift actor for thread-safe cache access."

Expected behavior: Do not prioritize platform-frontend; choose a more relevant skill or proceed without it.

Troubleshooting

Skill Does Not Trigger

  • Error: The skill is not selected when expected.
  • Cause: Request wording does not clearly match the description trigger conditions.
  • Solution: Rephrase with explicit domain/task keywords from the description and retry.

Guidance Conflicts With Another Skill

  • Error: Instructions from multiple skills conflict in one task.
  • Cause: Overlapping scope across loaded skills.
  • Solution: State which skill is authoritative for the current step and apply that workflow first.

Output Is Too Generic

  • Error: Result lacks concrete, actionable detail.
  • Cause: Task input omitted context, constraints, or target format.
  • Solution: Add specific constraints (environment, scope, format, success criteria) and rerun.

Workflow

  1. Identify whether the request clearly matches platform-frontend scope and triggers.
  2. Apply the skill rules and referenced guidance to produce a concrete result.
  3. Validate output quality against constraints; if gaps remain, refine once with explicit assumptions.
Weekly Installs
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GitHub Stars
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First Seen
Feb 11, 2026
Installed on
opencode29
gemini-cli29
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kimi-cli29