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Found 82 Skills
Minimal text embedding smoke test for Model Studio embedding models.
Official Google Search guidance for optimizing websites for generative AI features such as AI Overviews and AI Mode. Use when an AI agent needs to explain, audit, plan, or implement SEO work for Google AI Search visibility; evaluate AEO/GEO claims; advise on llms.txt, structured data, content quality, crawlability, JavaScript SEO, media SEO, ecommerce/local details, Merchant Center, Business Profile, or agent-friendly site readiness.
Optimize a listing for Amazon's AI shopping assistants (Rufus on the web, Alexa+ on devices, and the COSMO ranking layer behind them). Rewrites bullets as question answers, completes the Attributes section, models voice query anatomy, and reinforces with review-language. Use when a user asks about Rufus, Alexa+, AI shopping, AI-driven search, COSMO, conversational shopping, question-style queries, voice shopping, voice search, smart speaker discovery, or conversational query optimization. Trigger phrases. "Rufus", "Alexa+", "AI shopping", "AI search", "COSMO", "conversational query", "question answering", "voice shopping", "Alexa search", "voice query", "smart speaker", "conversational shopping". Works with zero tools.
Configure search result boosting in GrepAI. Use this skill to prioritize certain paths and penalize others.
Use when reranking search candidates is needed with Alibaba Cloud Model Studio rerank models, including hybrid retrieval, top-k refinement, and multilingual relevance sorting.
Advanced search options in GrepAI. Use this skill for JSON output, compact mode, and AI agent integration.
Use AliCloud Milvus (serverless) with PyMilvus to create collections, insert vectors, and run filtered similarity search. Optimized for Claude Code/Codex vector retrieval flows.
Use Parallel's parallel-cli to do live web search, URL extraction (clean markdown), deep research reports, bulk data enrichment (CSV/JSON), FindAll entity discovery, and web monitoring. Use when the user asks to look something up online, needs current sources/citations, provides URLs to read or summarise, requests deep/exhaustive research, wants to enrich a dataset with web-sourced fields, wants a list of entities (companies/people/places), or wants to monitor the web for changes over time.
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vectorization pipelines.
Build vector retrieval with DashVector using the Python SDK. Use when creating collections, upserting docs, and running similarity search with filters in Claude Code/Codex.
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. USE FOR: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech. DO NOT USE FOR: Function apps/Functions (use azure-functions), databases (azure-postgres/azure-kusto), general Azure resources.