812 件 ・ 関連度順
概要と使いどころ
Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content 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。
Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt presence (optional; ignored by Google Search), passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
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 positioning an AISTATS submission against AI, machine-learning, statistics, and uncertainty literature, including arXiv preprints, workshop versions, concurrent submissions, prior conference versions, PMLR archival status, and the two-community citation coverage that AISTATS reviewers expect.
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 positioning an American Anthropologist (AA) manuscript against the literature so it reads as a four-field contribution. AA readers span sociocultural, archaeology, biological, and linguistic anthropology, so the paper must engage the conversations they expect and decenter a US/Anglophone-only canon. Stakes the contribution and citational politics; it does not write the lit review.
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 or auditing the related-work section of an ACM MM (ACM Multimedia) paper — covering the multimedia literature spread across vision, audio/speech, language, HCI/QoE, and systems, handling arXiv-speed concurrency, keeping citations double-blind, and verifying that cited "ACM MM papers" are ACM MM and not ICMR, MMSys, CVPR, or TOMM.
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 or repairing the literature review for 《会计研究》 (Accounting Research) — entering the accounting research lineage (earnings quality, conservatism, audit quality, disclosure, value relevance) rather than piling recent Chinese empirical citations, and positioning the gap as an accounting contribution.
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 positioning an AAMAS submission against multiagent, game-theory, and reinforcement-learning literature spread across AAMAS, AAAI, IJCAI, NeurIPS, ICML, EC, and JAAMAS, including arXiv and workshop versions, concurrent submissions, prior conference versions, and the cross-community citation coverage AAMAS reviewers expect.
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。
Render pixel-accurate ChatGPT mobile (iOS) screen mockups in light mode from a thread JSON. Supports user text bubbles, user image attachments, assistant markdown prose, citation chips, the OpenAI spiral logo, the Apps-SDK GPT chip in the composer, and three header styles (model-tag, plain title, "Get Plus"). Fixed 9:16 viewport. Outputs HTML + PNG.
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 the user needs multi-source research with citation tracking, evidence persistence, and structured report generation. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not 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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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。
Optimize a prisma.io page for search engines and AI answer engines. Use when writing or reviewing blog posts, docs pages, or landing pages for SEO, GEO, AEO, AI citations, AI Overviews, ChatGPT/Perplexity visibility, featured snippets, metadata, or FAQ sections; when refreshing an existing page for freshness or rankings; or when asked why a page isn't ranking or being cited.
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。
Draft from the vault: outline from concept pages, keep citations to the user's own sources, and surface where their material disagrees. Use this skill when the user wants to write an article, post, essay or newsletter based on what they have collected, or asks what they could write about a topic. Do NOT use for research reports, for writing with no grounding in the vault, or for editing text the user wrote themselves unless asked.
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。
Produce a research report from the vault: scope the question against existing pages, name the gaps, and write findings with citations, disagreements and limits. Use this skill when the user asks for a research report, a deep write-up on a topic, or wants to understand a subject thoroughly using what they have collected. Do NOT use for a quick answer from the vault, for drafting an article in the user's voice, or for summarising a single source.
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。
Manage and verify references for mathematical modeling contest papers, generating BibTeX entries, checking citation completeness, and ensuring all references are traceable to actual sources.
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。
When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals," "citations," "references," or "credibility." For headings, use heading-structure.
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。
Parse current CNKI search results page into structured paper data (title, authors, journal, date, citations). Use after a search has been performed and you need to extract the results.
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。
Export paper from CNKI and push to Zotero, or save as RIS file. Use when user wants to save a paper to Zotero or export citation data.
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。
Expert GDPR compliance assistant covering all four core workflows: (1) auditing code and systems for GDPR violations, (2) drafting GDPR-compliant documents such as privacy policies, Data Processing Agreements (DPAs), and consent notices, (3) answering GDPR compliance questions with authoritative article citations, and (4) reviewing data flows and PII handling practices. Use this skill whenever the user mentions GDPR, data protection, privacy compliance, lawful basis, data subject rights, DPA, privacy notices, consent management, data breaches, DPIAs, controller/ processor relationships, cross-border data transfers, or any EU/UK data privacy topic. Also trigger for questions like "is this GDPR compliant?", "how do I handle personal data?", "what does a privacy policy need?", or any request involving PII, personal data, or data retention in a regulatory context.
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。
Compatibility entry point for researching a current topic into a source-backed Markdown brief and turning it into a Codex Slides outline or rendered deck. Use for market, competitive, policy, technical, academic, or other presentation requests that need current facts, figures, comparisons, or citations.
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 to "analyze this codebase", "document this service", "generate technical docs", "I inherited this code", "help me understand this system", "create docs for this project", "what does this system look like", "onboard me to this codebase", "this codebase has no docs", "visualize the architecture from code", or any explicit request to produce structured documentation or architecture diagrams from an existing codebase. Specifically optimized for AWS workloads (CDK, CloudFormation, Terraform) with source-of-truth citations. Do NOT activate for code reviews, single-function explanations, generating new code, or general coding tasks.
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。
Adversarial verification for AI-generated legal content. Use when fact-checking legal documents, validating citations, detecting hallucinations, scoring document quality, or assessing distribution readiness.
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。
Extract structured data from multiple documents into comparison matrix with citations. Use for bulk document review.
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。
Map the dark funnel attribution misses: communities, AI citations, podcasts, word of mouth. "map our dark funnel"
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。
Audit local SEO health by script: profile, NAP, citations, reviews, scored 0-100. "audit our local SEO"
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。