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159 indexed skills · max 10 per page
alicloud-ai-search-dashvector-test
cinience/alicloud-skills · Cloud
Category: test
tavily-search
tavily-ai/skills · Productivity
Web search with LLM-optimized results, content snippets, and relevance scores. \n \n Supports four search depths (ultra-fast, fast, basic, advanced) with configurable result counts up to 20, plus domain filtering and time-range constraints \n Returns structured JSON output with content snippets, relevance scores, and metadata optimized for LLM consumption \n Includes specialized search modes for news and finance topics, with optional AI-generated answers and full page content extraction \n Integ
loogle-search
parcadei/continuous-claude-v3 · Productivity
Search Mathlib for lemmas by type signature pattern.
search-first
affaan-m/everything-claude-code · Productivity
Systematize research-before-coding by searching existing tools, libraries, and patterns before writing custom code. \n \n Provides a five-phase workflow: need analysis, parallel search across npm/PyPI/MCP/GitHub, evaluation, decision (adopt/extend/compose/build), and implementation \n Includes a decision matrix to score candidates on functionality, maintenance, community, docs, license, and dependencies \n Offers search shortcuts organized by category (development tooling, AI/LLM integration, da
grepai-search-tips
yoanbernabeu/grepai-skills · AI/ML
This skill provides tips and best practices for writing effective semantic search queries.
alicloud-ai-search-opensearch
cinience/alicloud-skills · Cloud
Category: provider
nansen-search
nansen-ai/nansen-cli · Productivity
$21
firecrawl-search
firecrawl/cli · Productivity
Web search with optional full-page content extraction from results. \n \n Returns real search results as JSON with optional --scrape flag to fetch complete page markdown for each result, avoiding redundant fetches \n Supports filtering by source type (web, images, news), category (GitHub, research, PDF), time range (past hour/day/week/month/year), location, and country \n Use --limit to control result count and --scrape-formats to customize output formats when extracting full content \n Part of
hybrid-search-implementation
wshobson/agents · Productivity
Combine vector and keyword search for improved retrieval in RAG systems and search engines. \n \n Provides four fusion methods: Reciprocal Rank Fusion (RRF) for general use, linear combination for tunable balance, cross-encoder reranking for highest quality, and cascade filtering for efficiency \n Includes production-ready templates for PostgreSQL with pgvector, Elasticsearch with dense vectors, and custom Python pipelines with parallel search execution \n Handles score normalization, metadata f