調査、論文、教育、資格学習（4,131 件）
概要と使いどころ
APPLIES/consumes a `citation-diversifier` budget report (`output/CITATION_BUDGET_REPORT.md`) to inject *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate without citation dumps.
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。
Regression-check citation anchoring (citations stay in the same subsection) to prevent “polish drift” that breaks claim→evidence alignment.
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。
Curate reader-facing survey tables for the Appendix (clean layout + high information density), using only in-scope evidence and existing citation keys.
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 per-chapter (H2) writing briefs (NO PROSE) so the final survey reads like a paper (chapter leads + cross-H3 coherence) without inflating the ToC.
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。
Multi-route literature expansion + metadata normalization for evidence-first surveys.
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。
Synthesize the shortlist into a discussion-ready research idea brainstorm memo, writing `output/REPORT.md`, `output/APPENDIX.md`, and `output/REPORT.json`.
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 a broad paper candidate pool needs deterministic deduplication and a stable core set.
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 a tutorial module plan exists but each module still needs a verifiable teaching loop.
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-budget plan/report (`output/CITATION_BUDGET_REPORT.md`); does NOT edit the draft. Allocates an in-scope per-H3 budget (NO NEW FACTS) so drafts stop failing the global unique-citation gate; citation-injector applies it.
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。
Download a small corpus of open-access arXiv survey/review PDFs about agentic systems and extract text for style learning.
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。
Professional deep research report generation — multi-agent collaboration with parallel chapter writing, automatic latest-data targeting, multilingual output, and built-in quality checks.
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 Exa MCP for current web, code/docs, company, people, and page-fetch research. Prefer current hosted tool schemas and note deprecated 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。
Autonomous iteration loop: modify, verify, keep/discard against any metric
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。
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.
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。
Programmatic Tavily search with context isolation. Use when web search or extraction will return large results that need filtering, deduplication, or multi-step triage before they enter the model context. Use tavily-search for ordinary lookups and tavily-research for end-to-end cited 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。
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
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。
对照高可信度一手来源调查问题，并将发现以 Markdown 文件落库。当用户希望研究某个主题、收集文档或 API 事实、或把阅读跑腿交给后台 agent 时使用。
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。
Structured requirements elicitation for analysis requests. Use when scoping new analysis projects, clarifying ambiguous business questions, or documenting analysis acceptance criteria with stakeholders.
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。
Launch and continue the Volcengine AI Research survey workflow for concept testing, audience design, questionnaire drafting, interview guide generation, execution confirmation, progress checks, and result queries. Use this skill when the user wants to create, revise, confirm, execute, or follow up on a real AI research survey task in ABCompass instead of doing generic brainstorming, copywriting, translation, summarization, or broad market discussion.
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。
Post-process LaTeX project prose to improve readability through varied sentence and paragraph lengths. Removes filler phrases and unnecessary transitions while preserving all citations and semantic meaning. Use after drafting is complete, when sections read as monotonous or blocky.
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。
Write LaTeX ML/AI review articles for arXiv using the IEEEtran template and verified BibTeX citations. Use when writing, planning, or continuing an arXiv review/survey paper, or when validating and repairing citations in an existing LaTeX project.
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 "deep research", "research team", "comprehensive analysis", "research report", "investigate thoroughly", "compare X vs Y in depth", or needs synthesis across multiple sources with verification. It spawns a coordinated team of researcher agents across multiple rounds, with the lead triaging findings and creating targeted follow-up tasks. Scales from Focused (2 researchers, 1-2 rounds) to Comprehensive (4 researchers, 3-4 rounds with cross-verification). Do NOT use for simple lookups, debugging, or questions answerable with 1-2 searches.
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 performing web research beyond a simple single search -- looking into topics, comparing options, investigating questions, finding recommendations, or any task where effective use of Exa, Firecrawl, and Reddit tools matters. Triggers on "research", "look into", "investigate", "compare", "find out about", "search for", "find information", "what do people think about", "what are the best", "look up", or multi-source search tasks. Also invocable explicitly by deep-research team members via the Skill tool.
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 user asks about 印光大师, 净土, 念佛, 持名念佛, 十念法, 摄耳谛听, 老实念佛, 信愿行, 带业往生, 仗佛慈力, 自力他力, 竖出横超, 往生, 极乐, 阿弥陀佛, 净土三经, 敦伦尽分, 闲邪存诚, 因果报应, 文钞, 一函遍复, or wants teaching in 印光大师 Yinguang's voice. Triggers include "印光"、"文钞"、"老实念佛"、"信愿行"、"带业往生"、"仗佛慈力"、"横超竖出"、"都摄六根"、"净念相继"、"敦伦尽分"、"闲邪存诚"、"因果"、"十念法"、"摄耳谛听"、"一函遍复"、"净土三经"、"往生" — invoke whenever user's question touches Pure Land practice, Amitabha recitation, or faith-vow-practice, even without explicit request.
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。