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概要と使いどころ
Lightweight multi-agent research orchestration using one coordinator, three domain leads, and three lightweight research agents. Use for medium-size research, market scans, competitor comparisons, prior-art style exploration, report planning, and any task that benefits from parallel domain decomposition without running a full high-cost research lab.
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Conduct reproducible web searches and decision-oriented research across official sites, search engines, news, papers, forums, social platforms, and public datasets. Use when Codex must investigate a person, organization, product, market, technical resource, reputation, career choice, or other current topic; compare candidates; verify claims; collect dated citations; distinguish facts from inference and anecdote; or write an evidence-backed research report.
日本語の概要は準備中です。原文の説明を表示しています。
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRouter. Capabilities: research, fact-checking, grounded responses, knowledge retrieval. Use for: AI agents, research assistants, fact-c...
日本語の概要は準備中です。原文の説明を表示しています。
Global skills manager for Google Antigravity. Explore, search, install, and manage 300+ agent skills from the rmyndharis/antigravity-skills catalog using pure stdlib CLI tools.
日本語の概要は準備中です。原文の説明を表示しています。
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로.
日本語の概要は準備中です。原文の説明を表示しています。
Route Tavily web-search, extraction, mapping, crawling, and cited-research requests to the narrowest `tvly` command. Use for command-line Tavily work, installation checks, authentication setup, or choosing among the specialized Tavily skills.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.
日本語の概要は準備中です。原文の説明を表示しています。
Run programmatic Tavily search and extraction while filtering raw results outside the main agent context. Use for multi-step or high-volume research where titles, snippets, and selected passages should be curated before synthesis.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose and optimize Agent Skills (SKILL.md) with real session data and research-backed static analysis. Works with Claude Code, Codex, and any Agent Skills-compatible agent.
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Search and analyze Reddit discussions for market research, product feedback, and community insights using Xpoz. Use when asked to "search Reddit", "what does Reddit think about X", "Reddit feedback on X", "subreddit analysis", or "Reddit market research".
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
日本語の概要は準備中です。原文の説明を表示しています。
Kelly's market-intelligence desk (Busabase App-in-Skill). Merges passive competitor monitoring (Radar), agent-run deep research with approved briefs and cited reports (Research), and keyword/topic demand signals (Trends) over one Busabase-backed snapshot, watchlist, and review model. Use when the user invokes $kelly-radar or /kelly-radar, or asks for competitor monitoring, market intelligence, market research, research reports, trends, rising keywords, pricing changes, product launches, changelog diffs, competitor reviews, funding or hiring news, or opportunity triage.
日本語の概要は準備中です。原文の説明を表示しています。
Legal precedent App-in-Skill (Busabase-backed) desk for internal casebase search, local court-pattern analysis, similar-case packs, citations, and approval-gated research exports. Use when the user invokes $kelly-legal-precedent-desk, mentions 类案检索, 本地裁判尺度, 内部案例库查询, 案例查阅与收藏, precedent research, similar cases, legal research pack, or wants a Busabase-backed desk where lawyers review agent-prepared precedent findings before reuse.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize ToolUniverse skills for better report quality, evidence handling, and user experience. Apply patterns like tool verification, foundation data layers, disambiguation-first, evidence grading, quantified completeness, and report-only output. Use when reviewing skills, improving existing skills, or creating new ToolUniverse research skills.
日本語の概要は準備中です。原文の説明を表示しています。
提案書の論点・仮説に基づくデスクトップリサーチを実行するスキル。WebSearch/WebFetch、Browser Use、Deep Researchプロンプト生成の3層で情報収集し、論点ごとに主張・根拠・ソースを整理した調査レポートと仮説検証シートを出力する。「デスクリサーチを実行して」「初期調査をして」「デスクトップ調査を行って」「追加調査をして」などのリクエスト時に使用。ワークフローのStep 3（初期デスクトップ調査）およびStep 10（デスクリサーチ）に対応。
When the user requests information about academic benchmarks, datasets, or research papers, particularly in machine learning, deep learning, or logical reasoning domains. This skill enables systematic research of academic benchmarks by searching web sources, downloading and analyzing arXiv papers, extracting key metadata (number of tasks, training availability, difficulty levels), and compiling comparative summaries. It triggers on requests involving dataset comparisons, benchmark analysis, or academic paper research for table creation.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.
日本語の概要は準備中です。原文の説明を表示しています。
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
日本語の概要は準備中です。原文の説明を表示しています。
Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, or wants to start a local web UI for their docs.
日本語の概要は準備中です。原文の説明を表示しています。
Free AI search via Exa MCP. Web search for news/info, code search for docs/examples from GitHub/StackOverflow, company research for business intel. No API key needed.
日本語の概要は準備中です。原文の説明を表示しています。
Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.ai with advanced caching and compression. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with optimized performance.
日本語の概要は準備中です。原文の説明を表示しています。