Research, academic papers, education, and exam prep (4.2K skills)
Run Tavily's multi-source research workflow for comparisons, market analysis, literature-oriented exploration, or detailed cited reports. Use only when bounded search and extraction are insufficient.
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Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
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Activate for building or scaffolding web apps when the user is learning (e.g., todo apps, portfolios, dashboards).
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NotebookLM MCP server management - query notebooks, add from share links, handle auth, reset sessions. Use when working with Google NotebookLM notebooks for conversational research tasks.
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Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and helper script for reproducible notebook structure and safer editing.
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Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
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Review homework notebooks for completeness, reproducibility, safe execution, and academic-integrity boundaries.
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Review final-assignment materials for requirements, citations, AI-use disclosure, and data-analysis completeness.
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Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
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Expert en portail éducation (inscription, notes, diplômes, e-learning, universités DZ)
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Plateforme éducative — LMS, MOOC, certification, e-learning Algérie, MEN
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Build taste through volume of output, deliberate failure, and speed. Taste cannot be developed by watching. It's sharpened by making, failing, and making again. Use when designing practice routines, breaking through creative blocks, or helping someone move from analysis to execution.
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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".
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Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.
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Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.
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全リクエストの受け皿。質問・相談・調査・実装・修正・GitHubイシュー対応など、 あらゆる開発リクエストを受け取り、内容に応じて最適な対応方法を選択する。 「対応して」「直して」「やって」「見て」「確認して」「どう思う？」 「相談したい」「壁打ちしたい」等の汎用的な指示で発火する。
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Agent tool で複数のサブエージェントを並列起動する／エージェントチームを組成する前に、編成パターン（サブエージェント vs エージェントチーム、レビュアー Teammate の要否、各役割のモデル選択）を決定するためのガイドを適用する。トリガー：3 つ以上の Agent を並列起動する／タスク間に依存関係がある／チームメイト同士の相互通信が必要／設計や計画フェーズで複数視点が欲しい／ある成果物を別の成果物がレビュー・参照する構造になる。単発のサブエージェント呼び出しや、依存のない fire-and-forget な並列調査では発火しない。
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DDDに基づいたドメインモデルを設計します。戦略的設計（境界コンテキスト、ユビキタス言語）と戦術的設計（エンティティ、値オブジェクト、集約、ドメインサービス、ドメインイベント）を定義し、ヘキサゴナルアーキテクチャとの統合を行います。ScalarDBのトランザクション境界や管理テーブル分類の考慮事項を含みます。中間状態はresearch/に記録されます。
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3エージェント（researcher, analyst, scout）による並列要件分析 Council。peer-to-peer で相互検証し requirements.md を確定。「要件を整理して」「要件定義して」「現状分析して」「要件をまとめて」で発動。
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Add drawings, shapes, and a consistent markup experience using PaperKit. Use when integrating PaperMarkupViewController for markup editing, adding shape recognition, working with PaperMarkup data models, embedding markup tools in document editors, or building annotation features that need the system-standard markup toolbar. New in iOS 26.
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Produces thorough, multi-source cited research reports from web and news without paid APIs. Use when the user asks for deep research, landscape analysis, competitive intel, market research, or a cited report needing broad source coverage.
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NotebookLM でレポート・ブリーフィングを作成する。「NotebookLM レポート」「NotebookLM ブリーフィング」「NotebookLM 学習ガイド」「NotebookLM ブログポスト」などで起動。notebooklm-mcp を使用。
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NotebookLM でディープリサーチ（Web 調査）を実行する。「NotebookLM リサーチ」「NotebookLM で調査」「NotebookLM ディープリサーチ」「NotebookLM で調べて」などで起動。notebooklm-mcp を使用。
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This skill should be used when the user asks to "calculate inheritance shares", "法定相続分を計算", "相続分を出して", "相続割合", "誰がどれだけ相続する", "遺留分", or wants to compute statutory inheritance shares from a family tree.
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