1.1K skills · sorted by relevance
Find and remove stored content from cognee using its SDK, HTTP API, or CLI. Inspect documents before deletion, choose document or dataset removal, or keep raw files while clearing derived graph relationships and search vectors.
Install and configure the memory-tencentdb plugin for OpenClaw to retain and retrieve conversation information. Verify the setup through logs and searches, adjust memory settings, and troubleshoot missing recall or vector search results.
Generate photos, illustrations, product mockups, and other bitmap images, or edit existing pictures with background changes, object removal, and transparent cutouts. Use reference images to guide variations and save selected assets for the project.
Design hybrid search on AlloyDB by combining meaning-based search, keywords, and SQL filters. Turn requirements into architecture diagrams, database setup scripts, deployment guidance, and validation plans for search applications on Google Cloud.
Helps design semantic search and RAG, where an AI answers using retrieved documents. Covers embeddings, numerical representations of content, plus document splitting, search indexes, keyword search combinations, and evaluation of retrieval quality.
Build search and recommendation features with Pinecone, a managed database for numerical representations of content. Covers data loading, combined meaning and keyword search, filtering by attributes, and separating data by user.
Guides building AI applications that search documents before answering questions, an approach called RAG. Covers importing files and web data, creating searchable indexes, adding conversational interfaces, and evaluating whether answers match the retrieved material.
Build document search and AI retrieval workflows with Chroma, a database for numerical representations of text. Cover document storage, meaning-based search, metadata filters, persistence, and connections to LangChain and LlamaIndex.
Guides building chatbots and tool-using agents with LangChain. Covers conversation history, model provider integration, and RAG, which retrieves relevant documents to inform answers, plus tracing to inspect application behavior.
Record operations across multiple AI agents and connect events into a traceable history. Search records by tracking ID, time window, or responsible component to support audits and investigations, with local storage available when the vector database fails.
Create flat SVG illustration cards featuring one expressive person and one main prop. A defined palette, character proportions, reusable drawing parts, and visual checks help keep error pages, onboarding screens, and marketing illustrations consistent.
Crawl linked pages within a chosen website scope and collect clean text, Markdown, or HTML with page metadata. Use the resulting records as source material for AI search systems or chatbot knowledge bases.
Select technologies for AI and machine learning features in .NET 8+ applications. Get task-specific plans or implementation guidance for structured predictions, text generation, document retrieval, tool-using agents, and running pretrained models locally or in production.
Build advanced AgentDB workflows with database synchronization, multiple databases, and search that combines meaning with attribute filters. Covers similarity measures, diverse search results, and operational patterns for distributed AI applications.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.
Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.
Understand how Continuous Claude stores session memories, runs automatic actions at key events, and passes work between sessions. The skill explains the setup, relevant files, recall commands, and available database options.
Audit Claude Code skills, agents, hooks, and a database-backed memory system. It reports configuration problems and broken references by severity, and offers an optional fix mode for permissions, hook builds, and missing cache directories.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
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Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
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Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets. Triggers: "azure-search-documents", "SearchClient", "SearchIndexClient", "vector search", "hybrid search", "semantic search".
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Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET", "SearchClient", "SearchIndexClient", "vector search C#", "semantic search .NET", "hybrid search", "Azure.Search.Documents".
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Create managed Iceberg tables using Amazon S3 Tables (s3tables API namespace) with automatic compaction and snapshot management. Sets up table bucket, namespace, table, schema, Glue catalog registration, partitioning, IAM access control. Triggers on: create table, data lake table, analytics table, structured data storage, S3 Tables, Iceberg, Athena table, partitioning strategy, access permissions. Do NOT use for: importing files (use ingesting-into-data-lake), vector storage (use storing-and-querying-vectors), querying existing tables (use querying-data-lake), or locating existing table (use finding-data-lake-assets).
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Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Prepper); ai-assistant (natural language data exploration, incident investigation, root cause analysis). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, Solr, vector/k-NN/semantic/hybrid search, RAG, log analytics, PPL, trace analytics, ISM, FAISS, HNSW, Migration Assistant, UltraWarm, OR1, query my data, analyze logs, investigate errors, root cause analysis.
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