조사, 논문, 교육, 자격증 공부 (4.5천건)
试界TryWorld AI 口播视频的统一定位入口，覆盖口播全流程（选题/写稿/优化/出片）。涉及口播的请求都应触发：做口播/口播视频/口播稿/写口播稿/帮我选题/口播选题/这周做什么口播/AI 资讯盘点，或直接粘贴口播稿要求优化出片。自动识别两种模式：①直接给稿 → $tryworld-paper 优化并出片；②要选题 → $tryworld-topics 拉 AIHOT 资讯产选题清单 → 挑选 → 写稿 → 优化 → 出片。子命令：只要选题/只要写稿/只优化不出片。交付附四平台推荐发布时间。无需同时引用其他技能。
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Create branded 试界TryWorld AI-knowledge videos in the fixed "Paper Algorithm" (纸上算法) style with HyperFrames. Input is a Chinese voiceover script and optional images; output is a 16:9 horizontal video with Azure YunxiNeural (真·云希) voiceover, word-synced captions, ink/paper animations and unified transitions, an always-visible anti-counterfeit red seal, plus horizontal (4:3) and vertical (3:4) cover images and platform-optimized titles for Bilibili/Douyin/Xiaohongshu. Brand values are theme-driven (themes/paper-algorithm.json by default; custom brand themes supported — see references/theme-guide.md). Use when the user provides an AI 科普/教程/内容解读/知识分享 script and wants a TryWorld/试界 branded video, asks for the 纸上算法/Paper Algorithm style, wants a consistent script-to-video pipeline with covers and titles, or wants this pipeline with their own brand theme.
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Answer a factual question from the web, or enumerate what exists, with sources
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Research a question across web and academic sources and produce a cited report.
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Find academic papers on arXiv, with citation counts and BibTeX.
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`.agent/agents/` のエージェント定義を入口に、タスクを調査・計画・実装・レビュー・検証へ分担するスキル。ユーザーが「エージェント」「マルチエージェント」「orchestrator」「役割分担」「複数担当」などを求めたとき、または大きな変更で担当境界を決める必要があるときに使う。
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不具合報告（GitHub Issue、フォーラム投稿、社内報告）を起点に、調査・再現・修正・検証・記録までを一貫実行するスキル。症状の切り分け、原因仮説の整理、最小再現、修正実装、ExecPlan作成、PR下書き、ナレッジ追記が必要なときに使う。
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Use only for user-provided academic text, explicit scholarly claims, existing citations, or known bibliographies needing citations added, verified, replaced, extracted, or formatted. Supports claim-to-source matching, citation-support checks, replacements, and common academic citation formats. Do not use for general fact-checking, legal/journalistic citation work, open-ended 'find literature about X', topic-level exhaustive discovery, systematic-review corpus construction, PRISMA searches, or creating new research claims. Chinese: 为已有段落补参考文献、核验已有引用、替换错误引用、提取需引文论断、GB/T 7714 格式化.
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MMDで静止ポーズ、表情、短いモーション、アクセサリ配置を制作・修正する。mmd-mcpによる実機操作、モデル骨格・軸・付与・IKの読み取り専用調査、モデル別の姿勢調整、主要キーと補間の編集、連続プレビューを扱う。
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Build detailed buyer personas and audience profiles from research. Use this skill whenever the user mentions audience, buyer persona, ideal customer, target market, ICP, watering holes, 'who am I selling to', customer research, or audience profile. Also use when content feels unfocused or generic (that's an audience problem), when conversion is low because messaging doesn't resonate, when starting any new project (audience should be first), or when any downstream skill needs audience.md but it doesn't exist yet. Even if the user doesn't explicitly ask for audience research, trigger this if they're writing copy or building a landing page without a clear audience defined. Three approaches: Quick Profile, Persona Build, Community Mining.
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Research and analyze competitors to find positioning gaps and strategic opportunities. Use this skill whenever the user mentions competitors, competitive analysis, competitor teardown, market landscape, 'who else does this', 'how are we different', or competitor research. Also trigger when the user is entering a new market, when positioning feels weak or generic, when preparing for a launch, when any downstream skill needs competitors.md but it doesn't exist, or when the user asks about differentiation or market gaps. Even if the user just names a competitor casually ('what does X do?'), this skill likely applies. Three modes: Quick Scan, Deep Teardown, Gap Finder.
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Research companies, competitors, funding, news, leadership, and market context with Exa Agent and advanced search. Use when researching companies, competitor analysis, market research, or building company lists. Writes findings the caller can fold into brand/competitors.md or brand/landscape.md. Prefer this over ad-hoc web search for company deep dives. Distinct from competitive-intel (full brand competitive file methodology) - this skill is the Exa research engine those foundation skills should call.
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Scan the current market landscape and produce a ground-truth ecosystem snapshot. Chains /last30days for live research, validates with user, and writes brand/landscape.md with a Claims Blacklist that hard-gates all content generation. Use when: "landscape", "ecosystem", "market snapshot", "ground truth", "what's happening", "refresh landscape", "market trends", or before any content campaign to verify claims.
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Call Exa Search (POST /search) for semantic web retrieval with ranked results, filters, freshness, highlights/text, structured output, or streaming. Use when the agent needs open-ended web search, competitor discovery, news, people, or research papers and does not already have URLs. Prefer Exa MCP web_search_exa / web_search_advanced_exa when available; otherwise raw HTTP with EXA_API_KEY. NOT for known-URL extraction (use exa-contents or firecrawl) or multi-step list-building (use company-research / lead-generation / Agent API).
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Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.
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Generate enriched ICP-based lead lists with Exa Agent, including structured scoring and CSV output. Use when generating leads, building prospect lists, finding companies to sell to, outbound research, or ICP-based company discovery. Triggers on leads, lead gen, prospect list, find companies, ICP, outbound list. Distinct from lead-magnet (content asset that captures emails).
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根據使用者的文章或論文草稿，自動用 Semantic Scholar、Crossref、arXiv API 搜尋相關文獻，並查核既有引用(文獻是否真實存在、書目欄位是否正確、內容是否支持文中論點)，也能從主題出發寫出「每個宣稱都有真實文獻支撐」的帶引用文章；另含研究生工具組：文獻矩陣、領域地圖、research gap 偵測、閱讀筆記卡、引用完整性檢查、中英術語一致性、口試/審稿預演、新文獻追蹤、引用需求標記(annotate)、反面證據搜尋(counter)、證據強度評級(strength)、claim-evidence 總表(claims)、撤稿查詢(retract)。凡是使用者提到找文獻、找 paper、補參考文獻、查核引用、檢查 citation、驗證參考文獻、related work、literature review，貼文章要求配文獻、問「這段話有沒有文獻支持」、要求「寫一篇帶參考文獻的文章」、要整理文獻比較表、問已指名兩概念的交集有沒有人做過、要準備口試文獻答辯時，都要使用本 skill。本 skill 的 gap 指令只查證使用者已指名的 X 與 Y 交集；若使用者連題目都還沒有、需要生成並逐一淘汰候選方向，那是題目生成，不在本 skill 範圍(環境裝有 research-gap-hunter 時交給它，沒有就如實說明本 skill 只能查證已指名的交集)。本 skill 的 map 指令盤的是**文獻**——奠基文獻是哪幾篇、關鍵作者是誰、近三年往哪走；若使用者要的是「這個領域現在有哪些**做法**、每一種買到什麼付出什麼、哪些已經飽和」，那是技術盤點不是文獻盤點，交給 research-gap-hunter 的 landscape，沒有那個 skill 就如實說明本 skill 的 map 只回答文獻層的問題。
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AIがユーザーの判断を得る時の心得。質問の前に何を説明するか、何をどう訊くか、回答が無い時の扱い、ユーザーが判断した根拠の報告に誤りがあった時の扱いを定める。 決めきれない事をユーザーに訊く時、計画を書く時、調査の結果として新しい方向を提案する時、質問に回答が無いまま進めようとしている時、以前の報告の誤りに気付いた時に読み込む。
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Apply AI to market research. TRIGGERS - Use when user needs help with ai-market-research related tasks.
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Build AI market research systems. TRIGGERS - Use when user needs help with ai-market-researcher related tasks.
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Build AI tutoring systems with adaptive learning. TRIGGERS - Use when user needs help with ai-education-tutor related tasks.
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Design agricultural education. TRIGGERS - Use when user needs help with agricultural-education-program related tasks.
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Prepare for educational accreditation. TRIGGERS - Use when user needs help with accreditation-preparation related tasks.
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Write agency case studies. TRIGGERS - Use when user needs help with agency-case-study-writer related tasks.
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