1.4万 件 ・ 関連度順
概要と使いどころ
Use when sources must stay traceable across sessions and years, when each reference needs a passport recording where it was found, how it was verified, and where it is cited, or when a draft needs a cited-but-unverified sweep before submission.
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 AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind 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。
Use when a draft in Turkish, English, or both reads as AI-generated and needs revision that removes machine writing patterns and translation calques while preserving meaning, citations, statistics, and the author's voice.
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 paired tr.md and en.md files need a parity verdict, when titles, frontmatter, headings, or DOI sets may have drifted between languages, or when a bilingual document is approaching release and its translation coverage needs an audit.
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 adapting academic findings for a public audience (op-ed, social post, podcast) and the simplification must stay evidence-faithful, avoid overclaiming, respect embargoes, and disclose AI assistance.
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 study's materials, data, code, or preprint need an open-science release: license choice, a persistent DOI (Zenodo/OSF), README and metadata, and an access-and-embargo decision that respects ethics constraints.
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 authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.
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 researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.
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 study needs a preregistration or a frozen analysis plan, when confirmatory and exploratory analyses must be separated, or when every deviation from the registered plan must be logged before the result is reported.
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 reviewer comments arrive and each one needs a tracked decision, when a revise and resubmit letter must map every comment to a manuscript change, or when contradictory reviewer demands need evidence-based, editor-facing framing.
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 reference list needs APA 7 cleanup, when DOIs must be confirmed real against Crossref or PubMed, when the user asks whether AI-suggested citations actually exist, or when a manuscript needs a citation hygiene pass before submission or defense.
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 research proposal needs work packages, milestones, deliverables, a timeline, a risk register, and budget-justification scaffolding, while keeping scientific claims and feasibility honest and human-owned.
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 building slides, a poster, or a lightning talk from a manuscript, when a presentation must exist in Turkish and English, or when conference visuals need a traceability check so every number on a slide matches the analysis behind 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。
Use for the search-planning stage of a literature review, when database lanes and language layers must be chosen, when DOI coverage policy is unclear, or when inclusion and exclusion criteria need drafting before any source is read; not for running the screening and PRISMA pipeline of a formal review, which is prisma-scoping-review-pipeline.
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 research note system needs architecture, when MOCs, frontmatter standards, and retrieval patterns must be designed for years of work, or when an existing vault has outgrown its structure and must migrate without breaking years of links.
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 construct, scale, or key term crosses Turkish and English and conceptual equivalence must be audited: translation and back-translation, construct drift, and culturally bound meaning, before measurement or cross-cultural claims.
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 an ethics committee or IRB application involves AI anywhere in the pipeline, when KVKK, GDPR, or EU AI Act duties must be mapped to a study, or when consent and disclosure language about AI use needs drafting before submission.
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 before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.
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。
v3.0 — Refactored 2026-05-02 from a 4,168-line monolith into a lean SKILL.md (~400 lines) plus 15 modular reference files in references/. Detail content loads on demand — Claude reads only the reference files relevant to the current task.
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。
You are orchestrating a penetration test using Claude Code agent teams. You
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 background Claude sessions to explore and analyze business ideas. Say 'Idea: [description]' to trigger.
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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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。
Generative Engine Optimization (GEO) for AI search visibility. Optimize content to appear in ChatGPT, Perplexity, Claude, and Google AI Overviews. Use when optimizing websites, pages, or content for LLM discoverability and citation.
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。
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
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。