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SkillsMP has collected 60 skills from nguyenthienthanh/aura-frog. Open a skill to review its source and details.
Showing 40 of 60 collected skills.
Vision feedback loop for UI — render the running UI, screenshot it across viewports + dark mode, run deterministic gates then a multimodal critique against the design system, and iterate until it passes. Use after building or changing a UI component/page,…
UI/UX design expertise — component design, design system selection, responsive layout. Includes auto-detection from package.json and Context7 integration for library docs.
Generate a cohesive color-token system from ONE OKLCH brand hue — primary/secondary/background/foreground/muted/border with semantic light + dark, emitted as a Tailwind v4 @theme block or a CSS-variables fallback. Use when starting a design system, defining…
Anti-AI-slop taste layer for UI output — distinctive typography, dominant+accent color hierarchy, and implementation-matched polish. Use when building or restyling a UI/landing/component that should look designed rather than defaulted, or when the user asks…
Generate UI designs using Google Stitch AI with optimized prompts
Execute 5-phase TDD workflow for complex features. Use when the user invokes /run, asks to build/create/implement a feature, requests a complex multi-file change, or types 'fasttrack:'. Enforces phase gates, sprint contracts, and builder!=reviewer discipline.
Restrained, accessible web motion — Framer Motion declarative patterns and CSS-only staggered reveals for high-impact moments, always bundle-aware and reduced-motion-safe. Use when adding animation/transitions to a UI (entrance reveals, list stagger,…
CRITICAL: MUST run for EVERY message. Detects agent, complexity, AND model automatically. Without this, tasks route to wrong agents and use wrong models, degrading quality and wasting tokens.
5 techniques for different problem types. Use when stuck or facing complex challenges.
Structured thinking process for complex analysis. Supports revision, branching, and dynamic adjustment.
Angular 17+ gotchas and decision criteria. Covers signals vs observables, standalone patterns, and common pitfalls Claude gets wrong.
Designs RESTful APIs with endpoint naming, versioning strategies (URL path, header-based), pagination (offset and cursor), error response schemas, and OpenAPI conventions. Use when the user asks about REST API design, creating endpoints, URL structure, API…
Fast bug fixes with root cause investigation + TDD. Enforces 'no fix without root cause' discipline and verification protocol. Without this skill, fixes are applied at symptoms instead of sources, and bugs return.
Draft → generate verification questions → answer independently via tools → revise. Catches hallucinated facts in reports and reviews. MANDATORY for Phase 4 security/test claims. Paper: Dhuliawala et al. 2023.
6-aspect structured code review (security, architecture, error handling, test gaps, type safety, simplification) with calibrated scoring and per-aspect breakdown. Use when the user asks to review code, check a PR, review a pull request, audit changes before…
Detect and simplify overly complex code. Apply KISS principle - less is more.
L1-L4 conflict detection between a proposed T4 task and pending-confirm sibling tasks. L1 (file overlap) + L2 (function/region overlap) ship in v3.7.0-beta.2 as deterministic bash. L3 (semantic LLM) + L4 (architectural LLM) are stubbed for v3.7.0-rc.1.
Systematic debugging protocol for bugs that resist quick fixes. Use bisection, hypothesis trees, and scientific method when a bug isn't obvious from the stack trace. Goes beyond bugfix-quick for production-grade root cause analysis.
Create Architecture Decision Records (ADRs) and Runbooks for operational documentation.
Detects when a new project-level skill / rule / command would reduce friction. Asks the user for confirmation before creating anything. NEVER writes plugin-level files — only `.claude/skills/`, `.claude/rules/`, `.claude/commands/` in the user's project.
Classifies execution failures into F1-F5 (transient/local-logic/local-design/story-level/architectural). Outputs JSON with class, confidence, evidence, and recommended action. Deterministic rule-based classifier; no LLM call.
Flutter/Dart gotchas and decision criteria. Covers Riverpod vs BLoC, widget optimization, and platform-specific pitfalls.
Unified framework expertise bundle. Lazy-loads relevant framework patterns (React, Vue, Angular, Next.js, Node.js, Python, Laravel, Go, Flutter, Godot) based on detected tech stack.
Token-efficient git operations with security scanning and auto-split commits
Auto-create git worktrees for workflows. Isolate changes, merge on success, discard on failure.
Go gotchas and decision criteria. Covers error handling patterns, concurrency pitfalls, and interface design.
Laravel/PHP gotchas and decision criteria. Covers N+1 prevention, Eloquent traps, and migration safety.
Load agent definitions on-demand to reduce context usage. Only loads full agent when needed.
Analyze collected learning data from Supabase to identify success patterns, failure patterns, optimization opportunities, and agent performance trends.
On-demand audit of MCP usage. Reads .aura/security/mcp-audit.jsonl, surfaces blocked calls, rate-limit hits, suspicious input patterns. Companion to mcp-call-gate hook (which produces the audit log).
Guide safe database and code migrations with zero-downtime strategies.
Detect and navigate monorepos correctly. Use when working with repos containing multiple packages (pnpm/yarn/npm workspaces, Turborepo, Nx, Lerna). Ensures commands run in correct package scope, dependencies are routed properly, and cross-package changes are…
Next.js 14+ gotchas and decision criteria. Covers server/client boundary, caching strategy, and data fetching patterns Claude commonly gets wrong.
Node.js gotchas and decision criteria. Covers async pitfalls, Express/NestJS patterns, and common mistakes.
Systematic performance profiling and optimization. Use when performance issues are reported or suspected. Measure first, optimize second. Applies Pareto principle — find the 20% of code causing 80% of slowness, fix that, not the rest.
Identifies and resolves performance bottlenecks across frontend (Core Web Vitals, code splitting, lazy loading), backend (N+1 queries, async processing), and database (EXPLAIN ANALYZE, indexing strategies) layers. Use when the user reports slow code, latency…
Loads permanent_memory.md summary lines (≤120 always-loaded tokens, hard cap 200). Surfaces durable wisdom from past Epics into the current session. Silent if .claude/memory/ does not exist.
Ultra-compact Phase 1 requirements output. HARD CAP: 500 tokens.
Compresses a completed plan-tree branch into .claude/plans/archive/{NODE_ID}.summary.md. Removes the original node files (preserved by checkpoint history). Reduces always-loaded surface area as features ship.
Loads minimum hierarchical plan context (.claude/plans/) for current execution focus. Auto-invokes every session when plans exist. Stays under 800 always-loaded tokens regardless of plan tree size.