Performance
Performance profiling and optimization
ac-context-optimizer
by adaptationio
Optimize context usage for autonomous coding. Use when managing context window, prioritizing information, reducing token usage, or improving efficiency.
Smoke Test Critical Paths Skill
by FortiumPartners
Load: skills/smoke-test-critical-paths/REFERENCE.md (~10KB)
ac-memory-manager
by adaptationio
Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
agent-memory-system
by adaptationio
Persistent memory architecture for AI agents across sessions. Episodic memory (past events), procedural memory (learned skills), semantic memory (knowledge graph), short-term memory (active context). Use when implementing cross-session persistence, skill learning, context preservation, personalization, or building truly adaptive AI systems with long-term memory.
mobile-development
by samhvw8
"Cross-platform and native mobile development. Frameworks: React Native, Flutter, Swift/SwiftUI, Kotlin/Jetpack Compose. Capabilities: mobile UI, offline-first architecture, push notifications, deep linking, biometrics, app store deployment. Actions: build, create, implement, optimize, test, deploy mobile apps. Keywords: iOS, Android, React Native, Flutter, Swift, Kotlin, mobile app, offline sync, push notification, deep link, biometric auth, App Store, Play Store, iOS HIG, Material Design, battery optimization, memory management, mobile performance. Use when: building mobile apps, implementing mobile-first UX, choosing native vs cross-platform, optimizing battery/memory/network, deploying to app stores, handling mobile-specific features."
databases
by samhvw8
"MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries."
performance-optimization
by Kaakati
"Expert performance decisions for iOS/tvOS: when to optimize vs premature optimization, profiling tool selection, SwiftUI view identity trade-offs, and memory management strategies. Use when debugging performance issues, optimizing slow screens, or reducing memory usage. Trigger keywords: performance, Instruments, Time Profiler, Allocations, memory leak, view identity, lazy loading, @StateObject, retain cycle, image caching, faulting, batch operations"
Performance Optimization
by Kaakati
Performance optimization patterns for Flutter applications including widget optimization, memory management, profiling, and 60 FPS best practices
chrome-devtools
by samhvw8
"Browser automation via Puppeteer CLI scripts (JSON output). Capabilities: screenshots, PDF generation, web scraping, form automation, network monitoring, performance profiling, JavaScript debugging, headless browsing. Actions: screenshot, scrape, automate, test, profile, monitor, debug browser. Keywords: Puppeteer, headless Chrome, screenshot, PDF, web scraping, form fill, click, navigate, network traffic, performance audit, Lighthouse, console logs, DOM manipulation, element selector, wait, scroll, automation script. Use when: taking screenshots, generating PDFs from web, scraping websites, automating form submissions, monitoring network requests, profiling page performance, debugging JavaScript, testing web UIs."
testing-strategy-builder
by ArieGoldkin
Use this skill when creating comprehensive testing strategies for applications. Provides test planning templates, coverage targets, test case structures, and guidance for unit, integration, E2E, and performance testing. Ensures robust quality assurance across the development lifecycle.
debug:flutter
by SnakeO
Debug Flutter applications systematically with this comprehensive troubleshooting skill. Covers RenderFlex overflow errors, setState() after dispose() issues, null check operator failures, platform channel problems, build context errors, and hot reload failures. Provides structured four-phase debugging methodology with Flutter DevTools, widget inspector, performance profiling, and platform-specific debugging for Android, iOS, and web targets.
debug:tensorflow
by SnakeO
Debug TensorFlow and Keras issues systematically. This skill helps diagnose and resolve machine learning problems including tensor shape mismatches, GPU/CUDA detection failures, out-of-memory errors, NaN/Inf values in loss functions, vanishing/exploding gradients, SavedModel loading errors, and data pipeline bottlenecks. Provides tf.debugging assertions, TensorBoard profiling, eager execution debugging, and version compatibility guidance.
speckit-analyze-zh
by forztf
对spec.md、plan.md和tasks.md三个核心文档进行非破坏性跨工件一致性和质量分析。在任务生成后识别不一致、重复、模糊和规范不足的项目。触发词包括："speckit-analyze"、"speckit分析"、"文档一致性分析"、"规范分析"、"质量检查"、"工件分析"、"spec分析"、"plan分析"、"task分析"。
juce-best-practices
by yebot
Professional JUCE development guide covering realtime safety, threading, memory management, modern C++, and audio plugin best practices. Use when writing JUCE code, reviewing for realtime safety, implementing audio threads, managing parameters, or learning JUCE patterns and idioms.
debug:pytorch
by SnakeO
Debug PyTorch issues systematically. Use when encountering tensor errors, CUDA out of memory errors, gradient problems like NaN loss or exploding gradients, shape mismatches between layers, device conflicts between CPU and GPU, autograd graph issues, DataLoader problems, dtype mismatches, or training instabilities in deep learning workflows.
refactor:pytorch
by SnakeO
Refactor PyTorch code to improve maintainability, readability, and adherence to best practices. Identifies and fixes DRY violations, long functions, deep nesting, SRP violations, and opportunities for modular components. Applies PyTorch 2.x patterns including torch.compile optimization, Automatic Mixed Precision (AMP), optimized DataLoader configuration, modular nn.Module design, gradient checkpointing, CUDA memory management, PyTorch Lightning integration, custom Dataset classes, model factory patterns, weight initialization, and reproducibility patterns.
debug:swiftui
by SnakeO
Debug SwiftUI application issues systematically. This skill helps diagnose and resolve SwiftUI-specific problems including view update failures, state management issues with @State/@Binding/@ObservedObject, NavigationStack problems, memory leaks from retain cycles, preview crashes, Combine publisher issues, and animation glitches. Provides Xcode debugger techniques, Instruments profiling, and LLDB commands for iOS/macOS development.
refactor:pandas
by SnakeO
Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.
Fastapi Patterns
by AmnadTaowsoam
'FastAPI is a modern, fast (high-performance) web framework for building
context-optimization
by ken-cavanagh-glean
Apply optimization techniques to extend effective context capacity. Use when context limits constrain agent performance, when optimizing for cost or latency, or when implementing long-running agent systems.
debugging-strategies
by EngineerWithAI
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
big-data
by pluginagentmarketplace
Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads
performance
by 89jobrien
Comprehensive performance specialist covering analysis, optimization,
agent-memory-skills
by kimasplund
Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md configuration.