1.7만건 · 관련도순
Coordinate AI research from literature review to paper drafting. The skill alternates focused experiments with broader reviews of findings, tracks hypotheses and decisions, and uses specialist skills to carry out research tasks and prepare progress reports.
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Audit search performance, page speed, and site structure to investigate traffic drops and content gaps. Combine findings from Google Search Console and technical checks into practical improvements and a 30-day action plan.
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Find potential customers based on your product and ideal customer profile, a description of companies you want to sell to. Research each prospect, score its fit with supporting evidence, and compile reports and a CSV.
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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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Archive several OpenSpec changes together after reviewing their documents and task progress. The skill checks code to resolve overlapping specification updates, syncs the selected updates, and reports which changes were archived, skipped, or failed.
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Install and configure OpenSearch for storing, searching, and analyzing KubeSphere logs, events, audit records, and notification history. Adjust storage and memory, enable a visualization interface, and manage scheduled cleanup of old search indexes.
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Develop a vague research interest into a specific question and plan. Use 5W1H prompts, literature reviews, and analysis of unanswered questions to define hypotheses, required evidence, suitable methods, and a concrete next step.
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Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
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When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with verification.
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Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuningUse when "adding search to, algolia, instantsearch, search api, search functionality, typeahead, autocomplete search, faceted search, search index, search as you type, algolia, search, instantsearch, indexing, relevance, faceted-search, autocomplete" mentioned.
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Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports Anthropic's claude CLI, OpenAI's codex CLI, and Google's gemini CLI as agent harnesses (selected via --harness).
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Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).
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The original reddapi.dev Reddit search skill (vector search, semantic search, trends, subreddit discovery), no Reddit OAuth or app registration needed. This is the same engine now packaged as reddit-research with added market-research playbooks and a fuller pitch on semantic vs keyword search; reddapi is kept live under its original name for existing installs and works standalone. Use when the user says 'reddapi' by name, or wants a minimal drop-in Reddit search skill without the extra research-workflow guidance. For the expanded research-oriented version with query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads. For a bare API reference, see reddit-search-api.
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Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.
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Firecrawl의 `/search`를 앱과 에이전트 흐름에 통합하여 검색어로 후보 웹페이지를 찾고, 출처 선택과 본문 수집 여부 결정을 돕습니다.
Research recent X posts by narrowing dates, trusted accounts, and keywords. Compare posts with web search results, link to the original posts, and distinguish reported reactions from claims that lack independent confirmation.
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Run a persistent research workflow with a defined goal and explicit acceptance checks. It saves progress and finishes only when a recorded result passes either a validation script or an architect review of the research output.
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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.
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Automate Composio Search operations through Rube MCP, a connection for agent tools. Discover available actions and their required inputs, verify the service connection, and execute tasks using the tool definitions returned by the search.
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Turn papers, code, experiment logs, and notes into an ARA, a structured research package for AI agents. Organizes claims, evidence, verification plans, code stubs, and research decisions, then checks coverage and consistency across the generated files.
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Build searches with Qdrant that find similar content and filter results by attributes. The skill covers document retrieval for AI answers, vector storage, memory optimization, and distributed deployment for larger collections.
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Build a starting roadmap for student legal research, including likely statutes, case law topics, background sources, and search terms. Review uploaded research for gaps, while clearly marking suggested citations as unverified leads that students must investigate themselves.
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Search the web and specialized subject areas, run multiple searches in parallel, and extract page text from URLs. Use the bundled command-line tools to gather current information, check claims, and read beyond search snippets.
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Set up and run research that compares evidence across multiple sources, such as market studies, competitor analysis, or fact checks. The skill handles environment checks, installation guidance, research settings, progress reporting, final files, and recovery.
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