Loading...
Loading...
Found 245 Skills
Skill for operating PocketBase backend via REST API and Go package mode. Provides collection CRUD, record CRUD, superuser/user authentication, backup & restore, migration file generation (JS and Go), Go hooks, custom routes, and design guidance for API rules, relations, and security patterns. Use for requests related to PocketBase, pb_migrations, collection management, record operations, Go framework embedding, and backend design.
Non-glass SwiftUI APIs from WWDC 2025 (iOS 26, macOS 26, visionOS 26). Covers @Animatable macro, TextEditor with AttributedString/AttributedTextSelection/AttributedTextFormattingDefinition, FindContext, WebView/WebPage, UIHostingSceneDelegate, ToolbarSpacer, Slider ticks, windowResizeAnchor, dragContainer, draggable(containerItemID:), scrollEdgeEffectStyle, tabBarMinimizeBehavior. Use when building rich text editors, embedding web content, bridging UIKit scenes to SwiftUI, or configuring scroll edge effects and tab bar minimization. DO NOT use for Liquid Glass design patterns (use apple-liquid-glass-design), general Swift or pre-iOS 26 SwiftUI (use swiftui-ui-patterns).
Generate a standards-aligned browser favicon.ico from a user-supplied source image, embedding PNG rasters at 32×32, 48×48, and 180×180 in one ICO container. Use when the user asks to create a favicon, 生成 favicon、网站图标、从图片做 ico、favicon.ico、create favicon from image. 从用户提供的源图生成含 32/48/180 三档尺寸的 favicon.ico（ICO 内嵌 PNG）。若用户未上传或未指定可用源图，必须中止并提示上传/路径。
Redis vector search guidance covering HNSW vs FLAT algorithm choice, vector index configuration (dims, distance metric, datatype), filtered hybrid search combining vector similarity with TAG or NUMERIC filters, and the RAG retrieval pattern with RedisVL. Use when defining a VECTOR field in FT.CREATE, integrating embeddings (OpenAI, Cohere, sentence-transformers), tuning HNSW parameters (M, EF_CONSTRUCTION, EF_RUNTIME), building a retrieval-augmented generation pipeline, or filtering vector results by attribute.
This skill should be used to watch a long-running background job (ffmpeg/media encode, qmd or other embedding/vector-DB run, batch agent/LLM pipeline, or a real-browser/agent-browser daemon) until it finishes or wedges, then deliver a verdict (done, needs-attention, or blocked) plus the exact next command, without burning dozens of manual poll commands. Triggers on "babysit this job", "watch this until it's done", "ping me when the encode/embed/batch finishes", "is this background process stuck", "monitor this ffmpeg/qmd run", or any request to wait on a long-running process and be told when it's complete or hung.
Split text into contextual chunks for RAG/embedding pipelines. Document segmentation and section extraction using window, tfidf, punctuation, or hybrid strategies chosen by intent.
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
Use when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.
CLIP, SigLIP 2, Voyage multimodal-3 patterns for image+text retrieval, cross-modal search, and multimodal document chunking. Use when building RAG with images, implementing visual search, or hybrid retrieval.
Cluster vectors by similarity using npx ruvector k-means or density-based methods with labeled group summaries
Use OpenClaw MemX for long-term agent memory with self-learning, relationship graphs, and automatic maintenance
AI/ML APIs, LLM integration, and intelligent application patterns