リサーチ・学習のスキル

Test understanding of recently written or accepted code

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。

Compare different approaches to solve the same problem

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。

Autonomous improvement loop: scan codebase metrics, scaffold experiment files, run agent-driven iterations until metric improves

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。

Step-by-step explanation of a concept with progressive depth

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 the local Claude Code learning path, record evidence, and schedule evidence-based reviews.

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。

Interactive skill assessment with personalized learning path generation

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。

Extracts Google Search results page (SERP) data including organic results, paid ads, related searches, People Also Ask questions, AI Overview text, and total result count from google.com. Use when user mentions Google search results, SERP scraping, google search data, search engine results page, organic rankings, keyword SERP, Google SERP extraction, scrape Google search, Google search API alternative, SEO ranking data, paid search ads, PPC ads on Google, Google search monitoring, keyword research, search results export, check Google rankings, what shows up on Google, search engine scraper, google results checker.

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。

AI-powered web research assistant that leverages BrowserAct API to supplement restricted web access by searching the internet for additional information. Designed for OpenClaw and Claude Code.

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。

This skill helps users automatically extract structured news data from Google News via BrowserAct API. Agent should proactively apply this skill when users express needs like searching for news about a specific topic, tracking industry trends, monitoring public relations or sentiment, collecting competitor updates, getting latest reports on specific keywords, monitoring brand exposure in media, researching market hot topics, summarizing daily industry news, tracking media activities of specific individuals, retrieving hot events from the past 24 hours, extracting structured data for market research, monitoring global breaking news.

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。

Deep-crawl any website from start URLs, return per-page LLM-ready text/markdown/HTML plus metadata (title, description, author, language, canonical URL, OG) and in-scope outbound links. Use when user mentions deep crawl website, recursive crawl, crawl a whole site, scrape entire website, scrape docs site, scrape documentation, scrape knowledge base, scrape blog, build RAG corpus, build vector database from website, knowledge base for chatbot, GPT knowledge files, llms.txt, sitemap crawl, BFS crawl, scrape with depth or page limit, include exclude URL globs, remove boilerplate, strip navigation header footer, website to markdown, website to text, multi-page extraction, bulk page scraping, clean markdown from URL, docs site to markdown corpus, site to clean corpus. Also applies to building RAG pipelines, indexing a customer site, syncing docs into a vector store, generating training corpora from any docs hub, or expanding a single start URL into a clean corpus of every reachable in-scope page.

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。

This skill helps users automatically extract complete Markdown content from any website via the BrowserAct Web Search Scraper API. The Agent should proactively apply this skill when users express needs like extract complete markdown from a specific website, scrape the content of an article link, get the text from a target url, convert a webpage to markdown format, fetch the main content of a blog post, extract data from a given web page, parse the html of a website into markdown, download the readable text from a news article, obtain the content of a tutorial page, extract all the markdown text from any http or https url, scrape documentation from a web link, or grab the text of a single webpage.

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。

Produces a citation-grounded summary across one or more workspace source files for summaries, briefings, literature reviews, or comparisons.

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 Zotero is the literature source of truth and the project KB should receive source notes under Sources/Papers plus project-linked synthesis in Knowledge and Writing.

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。

This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning.

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 when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured Chinese/English summaries for selected papers.

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 review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.

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。

This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.

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 by default for non-trivial multi-step work that needs persistent planning, progress tracking, or durable notes on disk. Trigger when a task will likely span multiple tool calls, research steps, verification loops, or enough context that the plan should not live only in transient chat memory.

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 as the main Claude Scholar skill for a vault-first, project-scoped Obsidian research knowledge base rooted at Research/{project-slug}/. It owns bootstrap, routing, daily logging, hub/plan/index maintenance, registry updates, lifecycle actions, and lint orchestration.

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。

This skill should be used when the user asks for efficient communication, task reports, file-operation summaries, research discussion, study-note synthesis, planning, writing feedback, or responses that need conclusion-first structure, concrete evidence, risk disclosure, and useful next steps.

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。

Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English.

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。

This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.

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 for project-scoped literature review built on Sources/Papers, with synthesis landing in Knowledge, writing handoff in Writing, and the default literature canvas under Maps/literature.canvas.

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。

This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns.

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。