React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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NotebookLM Distiller: Batch knowledge extraction from Google NotebookLM into Obsidian. Supports Q&A generation (15-20 deep questions), structured summaries, glossary extraction, web research sessions, and direct markdown persistence.
Autonomously manage and use local Ollama models for continuous operation without internet dependency. Includes model health monitoring, automatic fallback, and self-healing capabilities.
Control Huawei HiLink USB LTE modems (E3372, E8372, etc.) via REST API. Send/receive SMS, check signal strength, manage SIM PIN, query prepaid balance, and monitor connection status. Use when sending or reading SMS messages, checking LTE signal/status, entering SIM PIN, querying mobile balance (USSD), or managing a HiLink USB modem.
Safety guardrails for autonomous agents. Intercepts destructive actions, requires structured approval before irreversible operations, with CLI-backed cryptographic audit trails and policy enforcement. Your lobster has claws. Keel is the rubber band.
Configure and use Volcano Engine (Volcengine) models including Doubao, GLM, Kimi, and DeepSeek. Use when: (1) Setting up Volcengine API access in OpenClaw, (2) Choosing between general vs coding endpoints, (3) Configuring model aliases for easy access, (4) Troubleshooting authentication or connection issues with Volcengine providers.
Integración con MemPalace para gestión de memoria semántica persistente. Use when you need to search, add, or query memories stored in a MemPalace palace. Supports semantic search, knowledge graph queries, and memory management via ChromaDB-based storage.
Perform 12-Factor App compliance analysis on any codebase. Use when evaluating application architecture, auditing SaaS applications, or reviewing cloud-native applications against the original 12-Factor methodology.
Extract architectural decisions from conversations. Identifies problem-solution pairs, trade-off discussions, and explicit choices. Use when analyzing session transcripts for ADR generation.
Vercel AI Elements for workflow UI components. Use when building chat interfaces, displaying tool execution, showing reasoning/thinking, or creating job queues. Triggers on ai-elements, Queue, Confirmation, Tool, Reasoning, Shimmer, Loader, Message, Conversation, PromptInput.
Reviews App Intents code for intent structure, entities, shortcuts, and parameters. Use when reviewing code with import AppIntents, @AppIntent, AppEntity, AppShortcutsProvider, or @Parameter.
Turn a set of local paths (or a beagle project's conventional knowledge locations) into a cited, structured extraction of insights, context, decisions, and raw detail.
Reviews axum web framework code for routing patterns, extractor usage, middleware, state management, and error handling. Use when reviewing Rust code that uses axum, tower, or hyper for HTTP services. Covers axum 0.7+ patterns including State, Path, Query, Json extractors.
Reviews BubbleTea TUI code for proper Elm architecture, model/update/view patterns, and Lipgloss styling. Use when reviewing terminal UI code using charmbracelet/bubbletea.
Reviews CloudKit code for container setup, record handling, subscriptions, and sharing patterns. Use when reviewing code with import CloudKit, CKContainer, CKRecord, CKShare, or CKSubscription.
Reviews Combine framework code for memory leaks, operator misuse, and error handling. Use when reviewing code with import Combine, AnyPublisher, @Published, PassthroughSubject, or CurrentValueSubject.
Automatic graph layout using dagre with React Flow (@xyflow/react). Use when implementing auto-layout, hierarchical layouts, tree structures, or arranging nodes programmatically. Triggers on dagre, auto-layout, automatic layout, getLayoutedElements, rankdir, hierarchical graph.
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
Core technical documentation writing principles for voice, tone, structure, and LLM-friendly patterns. Use when writing or reviewing any documentation.
Reviews Elixir code for idiomatic patterns, OTP basics, and documentation. Use when reviewing .ex/.exs files, checking pattern matching, GenServer usage, or module documentation.
Reviews Elixir documentation for completeness, quality, and ExDoc best practices. Use when auditing @moduledoc, @doc, @spec coverage, doctest correctness, and cross-reference usage in .ex files.
Reviews Elixir code for performance issues including GenServer bottlenecks, memory usage, and concurrency patterns. Use when reviewing high-throughput code or investigating performance issues.