Research Claude Skills
2 269 research skills from 396 authors. They find sources and get you up to speed on unfamiliar ground. Half of them fit into 2 278 tokens or less — that is what one costs your context window when the agent loads it. 663 ship runnable scripts rather than instructions alone. 4 of them cannot work without an MCP server, most often rube. We also found 264 copies of these same skills sitting in other people's repositories — counted once here, not 264 times.
2 269 unique 396 authors 1 169 updated this month 93 from vendors
Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple sessions.
> Discovery-scale research harness. A cheap scout maps the topic, the Lead designs topic-specific parallel researcher assignments from the scout's map (drawing on a source-class tactics library — academic, repos, production patterns, web, experts), then verifies claims against sources and writes a decision-oriented report. Use when brainstorming a project or feature, choosing a technology, or asked to "research X", "state of the art", "deep research". For narrow slice-level fact checks inside the build loop, /lead handles those inline.
Run a cumulative daily or retrospective sweep of research papers on a chosen topic, audit their claims, methods, integrity signals, and independent support, then identify overlooked but feasible project or business opportunities in a detailed source-grounded report. Use when asked to monitor papers every day, mine buried research, evaluate whether a paper is credible or reproducible, find unimplemented research ideas, or separate promising work from hype, weak evidence, and retracted or contradicted results.
Research and qualify business leads against your ICP
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
> Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Systematizes the "search for existing solutions before implementing" approach. Use when starting new features or adding functionality.
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
日本語翻訳：このファイルは market-research 用の日本語翻訳が必要です
証拠優先のecc現状調査ワークフロー。ユーザーが現在の公開証拠と提供されたローカルコンテキストに基づいて最新の事実、比較、情報の充実、または推奨事項を求める場合に使用する。
学術、生物医学、技術、科学的なトピックに対するシステマティックな文献レビューワークフロー。検索計画、ソースのスクリーニング、統合、引用確認、証拠ログを含む。
論文、提案書、文献レビュー、方法論セクション、証拠の質、引用サポート、研究論文フィードバックのための構造化された学術的作業評価。
Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.
使用firecrawl和exa MCPs进行多源深度研究。搜索网络、综合发现并交付带有来源引用的报告。适用于用户希望对任何主题进行有证据和引用的彻底研究时。
通过Exa MCP进行神经搜索，适用于网络、代码和公司研究。当用户需要网络搜索、代码示例、公司情报、人员查找，或使用Exa神经搜索引擎进行AI驱动的深度研究时使用。
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on OpenAI's March 2026 harness design paper.
进行市场研究、竞争分析、投资者尽职调查和行业情报，附带来源归属和决策导向的摘要。适用于用户需要市场规模、竞争对手比较、基金研究、技术扫描或为商业决策提供信息的研究时。
Evidence-first current-state research workflow for ecc. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.
研究优先于编码的工作流程。在编写自定义代码之前，搜索现有的工具、库和模式。调用研究员代理。
Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Search and monitor arXiv papers. Query by topic, author, or category. Track new papers, download PDFs, and summarize abstracts for research workflows.
BTC 5-minute Up/Down paper trading on Polymarket. Scans Binance 1m candles for momentum/mean-reversion/volume signals, makes virtual trades on Polymarket 5-min markets, tracks P&L. Use when: (1) scanning BTC 5-min trading signals, (2) running paper trade simulations, (3) reviewing 5-min strategy performance, (4) iterating scalping strategy parameters. Trigger: 'btc 5min', '5分钟', 'scalper', 'paper trade', '纸盘', '模拟盘'.
Call preparation: research, CRM, talking points, PDF
Semantic Similarity Index for disease research literature using PubMedBERT embeddings
Structured, multi-dimensional company investment research framework for AI agents and human analysts. Provides a 10-part checklist (moat, tech, market, customers, growth, financials, geography, governance, valuation, recommendation) to turn scattered info into a consistent, high-quality investment memo. | 面向 AI Agent 与人工分析师的公司投研框架，用 10 大维度系统梳理商业模式、护城河、成长与估值，快速产出结构化投研报告。
Generate competitive analysis reports and differentiation talking points based on secondary research
This skill synthesizes findings from 40 documented research sources
Research crypto news, public market data, and monitored accounts with CT Monitor. Use for attributed briefings, watchlists, narrative review, and paper-only signal analysis.
Perform structured investment research (投研分析) for a company/stock/ETF/sector using a repeatable framework: fundamentals (basic/财务报表与商业模式), technical analysis (技术指标与关键价位), industry research (行业景气与竞争格局), valuation (估值对比/情景), catalysts and risks, and produce a professional research report + actionable plan. Use when the user asks for: equity/ETF analysis, earnings/financial statement breakdown, peer/industry comparison, valuation ranges, bull/base/bear scenarios, technical trend/support-resistance, or a full research memo.
Research a topic from the last 30 days. Also triggered by 'last30'. Sources: Reddit, X, YouTube, Hacker News, Polymarket, web. Become an expert and write copy-paste-ready prompts.
Research topics, manage watchlists, get briefings, query history. Also triggered by 'last30'. Sources: Reddit, X, YouTube, web.
Legal demands two things: frontier-level reasoning and precision document generation. CellCog delivers both. #1 on DeepResearch Bench (Feb 2026) for the intelligence that legal work requires, paired with state-of-the-art document generation for contracts, NDAs, terms of service, privacy policies, compliance reviews, and legal research. AI contract generator, legal document drafting, NDA creator, terms of service, privacy policy, compliance, legal AI.
Search PubMed and bioRxiv, summarise papers with LLM, build citation graphs, and generate literature review sections.
Size markets, analyze competitors, and validate opportunities with practical frameworks and free data sources.
Team-wide memory routing skill — routes agent queries to the optimal knowledge source (QMD hybrid search, daily memory, MEMORY.md) and enforces citation. Use when any agent needs to retrieve prior work, system config, skill docs, project status, or decisions. Triggers on "查知识库", "memory router", "qmd query", "find in docs", "what was decided", "how does X work", "项目状态", "之前的决策".
Guide product managers through structured PRD (Product Requirements Document) creation by orchestrating problem framing, user research synthesis, solution definition, and success criteria into a cohes
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal impl...
为重要决策设计可证伪研究问题、检索协议、证据台账、反证矩阵、不确定性说明和带引用的综合结论。适用于比较竞争性解释、审查多来源主张、建立证据图或决定下一步研究；不用于无需研究的稳定常识、单纯数据查询、伪造来源，或未经授权购买资料、联系研究对象和访问受限内容。
四源同级：Brave (`web_search`) + Exa + Tavily + Grok。按意图自动选策略、调权重、做合成。 DEFAULT search tool for ALL search/lookup needs. Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis. Use for ANY query that requires web search — factual lookups, research, news, comparisons, resource finding, "what is X", status checks, etc. Do NOT use raw web_search directly; always route through this skill.
Expert web researcher using advanced search techniques and synthesis. Masters search operators, result filtering, and multi-source verification. Handles competitive analysis and fact-checking. Use PROACTIVELY for deep research, information gathering, or trend analysis.
Analyze Google SERP (Search Engine Results Pages) — featured snippets, PAA (People Also Ask), AI Overview, knowledge panels, local packs. Detect AI Overview trigger conditions and optimize content to be cited by AI. Use when user asks to 'analyze SERP', 'check search results', 'AI Overview analysis', 'featured snippet optimization', 'PAA research', or 'how to get cited by Google AI'.
You are an expert market researcher who uses LLM-generated synthetic survey responses and Semantic Similarity Rating (SSR) to produce fast, cheap, dir Fast, cheap market research using LLM-generated synthetic survey responses with Semantic Similarity Rating (SSR). Runs purchase intent, concept tests, and pricing research in minutes instead of weeks, at $0 per respondent. Based on PyMC Labs' validated methodology (90% correlation with real humans purchase intent, concept test, consumer research, SSR, synthetic survey, product validation, pricing research, Likert scale.