Results for “information-retrieval”

Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.

Guides selection of Qdrant search strategies including hybrid search, reranking, relevance feedback, MMR, and discovery APIs to improve retrieval quality.

Search arXiv papers by keyword, author, category, or ID.

Retrieves and answers questions from a local knowledge base directory by navigating hierarchical index files, then progressively searching Markdown, PDF, and Excel files using grep, Read, pdfplumber, and pandas.

Run evidence-first research, web/source search, Exa search, iterative retrieval, and research-before-coding workflows. Use when prompts ask for current facts, source-backed recommendations, market or company research, code/library discovery, query refinement, cited synthesis, deep research, or the old deep-research/research-ops/exa-search/iterative-retrieval/search-first skills.

Search arXiv papers by keyword, author, category, or ID.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Search and retrieve academic papers from arXiv via their REST API, including citation data from Semantic Scholar.

Search arXiv papers by keyword, author, category, or ID.

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Use this skill for search indexing, embeddings, RAG chunking, freshness, retrieval evaluation, source citations. Trigger when the task involves ai engineering work related to Search Indexing RAG, implementation, audits, debugging, strategy, or validation.

Search arXiv papers by keyword, author, category, or ID.

Search arXiv papers by keyword, author, category, or ID.

Search arXiv papers by keyword, author, category, or ID.

Turn accepted search evidence into an intent, competitor, and information-gain brief.

Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content.

Use before starting any new work to check for existing knowledge. This skill provides a systematic search and retrieval process for finding relevant knowledge from memory systems (PARA, Gigabrain, OpenStinger, existing skills) before starting work, preventing redundant effort and leveraging prior learning.

Master the AI tools that accelerate research and information gathering. From market research to academic analysis, find insights faster and make better decisions. Use when "research, find information, academic papers, market research, competitive intelligence, fact check, research, information, analysis, academic, market-research" mentioned.

Answers factual questions by searching the web, fetching primary sources, and cross-checking claims before citing them.

Guides database index selection, creation, and maintenance with SQL examples for PostgreSQL and MySQL.

Locates files by name and searches file contents using the fd and ripgrep command-line tools.

Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content.

Look up current research and scientific information across three backends: fast web search, deep multi-source synthesis, and scholarly paper searches. Automatically routes each query to the best backend and saves every result for reproducible citation.

Search the web, extract URL content, enrich datasets with web-sourced fields, and run deep research reports, prioritizing academic and scientific sources.

Search the web and extract content from URLs using Exa, with support for academic and scientific sources.

Run STORM phase 1 — multi-perspective research. This skill should be used when the user asks to "research a topic for an article", "find sources on X from multiple perspectives", "do storm research on X", or invokes /storm:research. Discovers personas, runs simulated Q&A per persona in parallel, and produces an information table + deduplicated sources.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Tavily web search, content extraction, and research tools.

Query documented public database APIs with explicit endpoints, filters, pagination, and provenance for reproducible retrieval of scientific, regulatory, or financial facts.

Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.

Search 10 academic literature APIs for papers, preprints, citations, and open-access full text with reproducible provenance.

research-synthesis

当需要获取独特信息源以产生差异化想法时