「citation」の検索結果

Use when a task needs the judgment of an Administrative Law Judge, Adjudicator, or Hearing Officer — applying a mandatory sequential/structured evaluation framework in required order, weighing conflicting medical or vocational opinion evidence using specific regulatory factors, writing findings that explicitly address significant contrary evidence in the record, drafting a credibility/consistency finding tied to specific record citations, or checking whether a draft decision would survive substantial-evidence review.

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Generate proper ENCODE citations for publications, grants, and presentations. Use when the user needs to cite ENCODE data, create bibliography entries, write acknowledgment sections, or ensure compliance with ENCODE data use policy.

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. GEO analysis enriched with Ahrefs Brand Radar AI visibility data when available. Includes brand mention signals, AI crawler accessibility, llms.txt compliance, 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", "AI visibility", or "Brand Radar".

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。

Content quality and E-E-A-T analysis with AI citation readiness assessment. Enhanced with live Ahrefs (actual keyword rankings, positions) and GSC (search query performance) data to validate static E-E-A-T analysis with real user behavior. 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 answer engines (AEO/GEO): citation-friendly structure, factual precision, and measuring AI visibility. Use when AI search drives discovery.

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。

Evidence-first academic research workflow for topic ideation, scholarly search, paper reading, literature and systematic reviews, study and experiment design, statistics and data analysis, scientific figures, manuscript drafting and polishing, citation checks, peer review, rebuttals, submission packages, theses, and paper-to-presentation work. Use when an agent must plan, execute, audit, write, revise, or package research while keeping claims traceable to verified sources, data, analysis, or official requirements.

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。

Generate a 2026-grade content brief for a target query — combines classic SERP analysis with AI Overview / Perplexity / ChatGPT citation analysis, entity recommendations (target ≥15 recognized entities), topical authority gap map, intent-mapped heading structure, internal linking targets.

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。

Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.

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Write new blog articles from scratch optimized for Google rankings and AI citations. Generates full articles with template selection, answer-first formatting, Key Takeaways summary box, information gain markers, evidence-backed explanations, sourced statistics, Pixabay/Unsplash images, built-in SVG chart generation, optional FAQ sections, internal linking zones, and proper heading hierarchy. Supports MDX, markdown, and HTML output. Use when user says "write blog", "new blog post", "create article", "write about", "draft blog", "generate blog post".

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。

Evaluate page content for usefulness, E-E-A-T, readability, thinness, and AI citation readiness, plus last-mile draft cleanup (AI-typical phrasing and invisible Unicode watermark characters). Use for content-only analysis, not full-page technical checks.

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, including Google Business Profile, NAP consistency, citations, reviews, local schema, location pages, and multi-location 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。

Generate detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, evidence-backed section planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citation visibility as part of SEO. Use when user says "content brief", "blog brief", "write brief", "SEO brief", "article brief", or "content requirements".

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 and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes advisory editorial style diagnostics (sentence-length variation, configured phrase lists, vocabulary sampling) that never infer authorship or affect scoring. Supports export formats (markdown, JSON, table) and batch analysis with sorting. Generates prioritized recommendations (Critical/High/Medium/Low) with specific fixes. Works with any format (MDX, markdown, HTML, URL). Use when user says "analyze blog", "audit blog", "blog score", "check blog quality", "blog review", "rate this blog", "blog health check".

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。

Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".

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。

Full-site blog health assessment scanning all blog files for quality scores, orphan pages, topic cannibalization, stale content, and AI citation readiness. Runs canonical batch analysis before site-wide checks. Produces per-post scores and a prioritized action queue. Use when user says "audit blog", "blog audit", "site audit", "blog health", "audit all posts", "check all blogs".

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。

Help authors learn from exemplary ICLR, ICML, and NeurIPS papers through source-linked manuscript comparisons, concrete writing and experiment suggestions, and guided reflection. Use for research storytelling, contribution framing, paper comparison, figure planning, or research retrospectives. Not an acceptance predictor or a routine grammar/citation formatter.

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。

Edit academic prose in LaTeX manuscripts or supplied text at light, moderate, or strict intensity. Improve grammar and clarity while preserving scientific claims, uncertainty, numbers, citations, and LaTeX 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。

Reconstruct editable LaTeX from PDF content using page-aware extraction and visual comparison. Preserve source evidence, flag uncertain math/tables/citations, and distinguish text extraction, OCR, reconstruction, and verified compilation.

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。

Read-only repository explorer. Use PROACTIVELY for cold-start exploration, broad cross-file localization, or when a direct search has failed and you need to find where something lives. Skip it when the issue already names the exact file or symbol, or a previous turn already returned usable file:line evidence. Returns only compact path:line citations; its reads and greps never enter the main conversation.

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 this skill when authoring INVEST-compliant Salesforce user stories from gathered requirements: shaping the As-A/I-Want/So-That stem, writing Given-When-Then acceptance criteria, sizing complexity (S/M/L/XL), splitting stories that are too large for a sprint, and emitting handoff metadata that names the next downstream agent. Trigger keywords: user story, INVEST, story splitting, story sizing, As-A I-Want So-That, story handoff, recommended_agents, backlog item shape. NOT for requirements elicitation or stakeholder interviews (use admin/requirements-gathering-for-sf). NOT for the Given-When-Then technique itself in depth (use admin/acceptance-criteria-given-when-then). NOT for UAT test case design (use admin/uat-test-case-design). NOT for backlog prioritization (use admin/moscow-prioritization-for-sf-backlog).

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 this skill when building, reviewing, or refreshing a RACI (Responsible / Accountable / Consulted / Informed) matrix for a Salesforce project so that every Salesforce-specific decision — data model change, automation tier choice, security model, integration boundary, deployment, license/edition — has exactly one accountable owner and a documented escalation path that downstream agents can route to. Trigger keywords: RACI matrix salesforce project, stakeholder authority salesforce, escalation path salesforce decisions, who approves data model change, salesforce decision rights, REFUSAL_NEEDS_HUMAN_REVIEW routing. NOT for the change advisory board operating model itself (use admin/change-management-and-deployment). NOT for end-user training rollout plans (use admin/change-management-and-training). NOT for the technical mechanics of permission set assignment authority (use admin/permission-set-architecture). NOT for pure stakeholder requirements elicitation (use admin/requirements-gathering-for-sf). More trigger keywords: who approves a sandbox refresh, who signs off a data load, release update activation owner, delegated admin authority vs RACI, multi-org decision rights, escalation time-box.

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Eliciting, documenting and structuring requirements for a Salesforce implementation: stakeholder discovery interviews, As-Is and To-Be process mapping, and gap analysis against standard Salesforce capability. Trigger keywords: requirements gathering, user story, As-Is To-Be, gap analysis, stakeholder interview, process mapping, business requirements, fit gap. NOT for authoring the user stories themselves - use admin/user-story-writing-for-salesforce. NOT for scoring requirements against a specific org - use admin/fit-gap-analysis-against-org. NOT for technical design decisions - use architect/solution-design-patterns. Also covers the requirements catalogue itself (one row per requirement, MoSCoW priority, source stakeholder, downstream target) and Salesforce non-functional requirements: record volume, sharing layer, integration pattern, reporting joins, mobile/offline, and licence implication.

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Use when scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).

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。