Skill profile

uniwind

Uniwind best practices for React Native styling with Tailwind CSS.

What this skill does for you

Uniwind best practices for React Native styling with Tailwind CSS. This skill should be used when writing, reviewing, or refactoring React Native code using Uniwind. Triggers on tasks involving Uniwind, className styling, Tailwind in React Native, NativeWind migration, or theming.

Quoted from the skill description in the pinned source

Who made it

Publisherpproenca

Repositorydot-skills

Installs332as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the uniwind skill from pproenca/dot-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: cf93c57cac89d6fc3e4194686000411567f5caf3. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: cf93c57cac89d6fc3e4194686000411567f5caf3. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: cf93c57cac89d6fc3e4194686000411567f5caf3. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/pproenca/dot-skills
Pinned skill file: View source at revision
Revision: cf93c57cac89d6fc3e4194686000411567f5caf3
Package hash: sha256:cc438843c7bf295e4e14fb3027b95b82e8fb067da7034fb05dc54015812b6610
Licence: MIT