调研、论文、教育、考证学习（4396 个）
- Investigator OPSEC — threat-model who might notice you, control your attribution surface across IP, ASN, browser and TLS fingerprint, timing and logged-in accounts, separate research identity from… Use when setting up a research account, avoiding tipping off a subject, worrying about LinkedIn profile-view leakage, needing a burner phone or email, or hardening a research VM or browser profile
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Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.
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- Build a sourced, corroborated profile of a named individual from public records, social platforms, professional networks, court and property filings, licensing boards, patents, papers and obituaries — anchoring the name to a… Use when asked to find, identify, background-check or profile a person, verify someone's claimed employment or credentials, or locate a missing or hard-to-reach individual
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ДР-ПОЛОСА — превратить наши дипресёрчи в 10 тизеров в день и разослать их по каналам лаборатории. Триггеры “/dr-teasers“, “/dr-lane“, “тизеры по ресёрчам“, “разошли дипресёрчи“, “10 тизеров“, “полоса дипресёрчей“, “post research teasers“, а также САМА ежедневная рутина “Claude DR Teasers Daily“
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Finds free backlink and brand mention opportunities across Hacker News, Quora, GitHub, directories, and niche communities. Outputs a prioritized action plan with draft responses ready to post. Use after brand research and content creation to amplify reach and AI engine citations.
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Decision protocol for strategic work: recall the knowledge vault, run a gap analysis, emit a deep-research prompt for external tools, then synthesize the returned reports into a decision memo. Use before any new product, feature, market, pricing, GTM or architecture call, where local recall alone is not enough. Triggers: "/alfa-search-recall-deepresearch", "alpha protocol", "R+DR".
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VRChat エコシステムツール（ModularAvatar / liltoon / VRCFury / AvatarOptimizer 等）の ナレッジを 4 フェーズで段階的に調査・検証し `knowledge/*.md` に再現可能な形で蓄積する。 ソースコード読解 → inspect 実測まで進めると confidence を `high` に昇格できる。 トリガー: 新しい VRChat コミュニティツールに初めて遭遇した、 既存ナレッジの confidence が low で作業に支障がある、 ユーザーから「このツールについて調べて」と依頼された場合。
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壊れた GUID / fileID 参照を検出し、一意な置換先のみ `safe_fix`、それ以外は `decision_required` で保留する。ignore-guid file (`<scope>/config/ignore_guids.txt`) と allowlist branch 経由で noise を整理する。 トリガー: `validate_refs` で missing GUID / fileID が出た、Broken PPtr の調査。
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Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.
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Manages government affairs, public policy communications, and collective action aligned with B Corp GACA standards. Creates policy position papers, advocacy communications, regulatory response documents, and transparent lobbying reports. Use when user asks about government relations, public policy, advocacy, lobbying, regulatory affairs, collective action, or political engagement transparency.
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Zotero ローカル API + REST API (Web API v3) 連携スキル。DOI からの文献一括インポート、コレクション管理、アイテム検索・一覧表示を行う。 REST API 経由でコレクション作成・アイテム CRUD・タグ管理・添付ファイルアップロード・グループライブラリ操作も可能。 Use when: (1) DOI リストから Zotero に文献を登録する, (2) Zotero のコレクション一覧・アイテム一覧を取得する, (3) BibTeX/RIS データを Zotero にインポートする, (4) CrossRef API で文献の DOI を検索する, (5) REST API でコレクション作成・アイテム追加・タグ管理を行う, (6) グループライブラリを操作する。 Triggers: "zotero", "文献登録", "DOI インポート", "コレクション", "論文追加", "文献管理"
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Use when revising or reviewing scientific, technical, or academic manuscripts, proposals, abstracts, reports, or related writing for precision, concision, logical cohesion, citation support, evidence alignment, and objective scholarly tone.
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Isolated codebase exploration that preserves your main context. Use when you need to understand code structure, trace call paths, or gather evidence before making changes. Spawns an explorer subagent.
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Evidence-first intent elicitation. Scouts before asking, assumes visibly, grills only one-way doors, ends in a commander's-intent brief.
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Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.
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Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.
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Standard Operating Procedures for read-only codebase exploration, symbol search, dependency mapping, code tracing, code review, architecture analysis, technical research, source evaluation, and evidence-based reporting.
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Conduct a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.
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Product-discovery coach for Fishbowl engineers — inspired by Marty Cagan's work (never impersonates him). Stage-routes between opportunity brief, research, PRD, ticket drafting, and outcome review. Triggers on "product coach", "help me with product", "I need to write a PRD", "I want to do discovery", "opportunity assessment", "who is this for", "why are we building this", or when an engineer is starting, resuming, or post-mortem-ing product-adjacent work. Invoke with a short description of what you want to do, or invoke bare to be surveyed and routed.
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Save the latest learning as a numbered markdown file under ~/.claude/learnings and update the learnings index with title and tags. Use when the user says "save", asks to record a learning, or wants the current insight stored for later.
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Multi-agent web research with cross-fact-checking and verified synthesis.
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Blind dual-implementation pattern where two agents independently create artifacts, then a third agent judges which is better and synthesizes learnings.
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Development skill from everything-claude-code
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Tokenizador agnóstico de linguagem que trata texto como Unicode bruto. Suporta algoritmos BPE e Unigram. Rápido (50k sentenças/seg), leve (6MB de memória), vocabulário determinístico. Usado por T5, ALBERT, XLNet, mBART. Treina em texto bruto sem pré-tokenização. Use quando você precisar de suporte multilíngue, linguagens CJK ou tokenização reproduzível.
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