Total 40,377 skills
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Evaluate the probability and path of copper prices breaking through key levels or entering a 'back-and-fill' pullback to support levels using cross-asset signals (global stock market resilience + Chinese interest rate environment).
Use when porting OpenGL/DirectX to Metal - translation layer vs native rewrite decisions, migration planning, anti-patterns
Expert-level Swift development for iOS, macOS with SwiftUI, Combine, and modern Swift 5.9+
Analyzes code to identify untested functions, low coverage areas, and missing edge cases. Use when reviewing test coverage or planning test improvements. Generates specific test suggestions with example templates following amplihack's testing pyramid (60% unit, 30% integration, 10% E2E). Can use coverage.py for Python projects.
Extracts key learnings from conversations, debugging sessions, and failed attempts. Use at session end or after solving complex problems to capture insights. Stores discoveries in memory (via amplihack.memory.discoveries), suggests PATTERNS.md updates, and recommends new agent creation. Ensures knowledge persists across sessions via Kuzu memory backend.
Measure the valuation range (overvalued/undervalued) of the mining stock sector relative to the metal itself using the ratio of Silver Mining Stock Price to Silver Price, and derive 'bottom/top' signals and scenario projections through historical percentiles and analogous intervals.
Enables Claude to manage YouTube channel, upload videos, and analyze creator analytics
Explore state management in Flutter, from the basics of `setState` to advanced techniques using ValueNotifier, Signals, Flutter Hooks, and the new signals_hooks package for a reactive and efficient approach.
Expert guidance for Jotai state management in React applications. Provides best practices, performance optimization, and architectural patterns. Use when designing atom structures, implementing state management, optimizing re-renders, handling async state, integrating with TypeScript, or reviewing Jotai code for performance issues. Triggers on tasks involving Jotai atoms, derived state, focusAtom, splitAtom, atomFamily, or state management architecture decisions.
Synthesize evidence into a structured narrative (`output/SYNTHESIS.md`) grounded in `papers/extraction_table.csv`, including limitations and bias considerations. **Trigger**: synthesis, evidence synthesis, systematic review writing, 综合写作, SYNTHESIS.md. **Use when**: systematic review 完成 screening+extraction（含 bias 评估）后进入写作阶段（C4）。 **Skip if**: 还没有 `papers/extraction_table.csv`（或 protocol/screening 尚未完成）。 **Network**: none. **Guardrail**: 以 extraction table 为证据底座；明确局限性与偏倚；不要在无数据支撑时扩写结论。
Write Metal/MPS kernels for PyTorch operators. Use when adding MPS device support to operators, implementing Metal shaders, or porting CUDA kernels to Apple Silicon. Covers native_functions.yaml dispatch, host-side operators, and Metal kernel implementation.
Performs pre-deployment checks ensuring code quality and environment readiness. Use when the user mentions deploying, shipping, or production releases.