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Found 1,845 Skills
Guidance for data resharding tasks that involve reorganizing files across directory structures with constraints on file sizes and directory contents. This skill applies when redistributing datasets, splitting large files, or reorganizing data into shards while maintaining constraints like maximum files per directory or maximum file sizes. Use when tasks involve resharding, data partitioning, or directory-constrained file reorganization.
Search data using vector similarity, full-text keywords, or hybrid methods with Reciprocal Rank Fusion (RRF). Use when setting up embeddings for search, configuring full-text indexing, writing vector_search/text_search/rrf SQL queries, using the /v1/search HTTP API, or configuring vector engines like S3 Vectors.
Shipp is a real-time data connector. Use it to fetch authoritative, changing external data (e.g., sports schedules, live events) via the Shipp API.
Extracts frames at regular intervals from dashcam videos to create compact visual summaries of vehicle movement and location changes. This skill should be used when users need motion trajectory analysis, want to optimize dashcam storage by 90%+, need quick visual review of hours of footage, or want to create visual timelines of trips.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.
Integrate Cartridge Controller wallet into Starknet applications. Use when setting up Controller for the first time, installing packages, configuring chains/RPC endpoints, or troubleshooting basic integration issues. Covers installation, Controller instantiation, ControllerConnector vs SessionConnector choice, chain configuration, and package compatibility.
Meta-prompting framework for critiquing responses, analyzing solution trajectories, and evaluating AI-generated content quality
Use when the user wants embeddings, vector indexing, retrieval, or retrieval-backed answers, including embedding-agent setup, Chroma-backed collections, collection add/query, and KB-to-answer flows.
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Expert knowledge for Azure AI Search development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing indexes, skillsets, vector/semantic search, indexers, private endpoints, or RAG apps, and other Azure AI Search related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics).
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
Curated documentation reference for developers building with Pinecone. Contains links to official docs organized by topic and data format references. Use when writing Pinecone code, looking up API parameters, or needing the correct format for vectors or records.