「technical」の検索結果

Comprehensive SEO analysis for any website or business type. Full site audits, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, content quality (E-E-A-T), image optimization, sitemap analysis, and GEO for AI Overviews/ChatGPT/Perplexity. Industry detection for SaaS, e-commerce, local, publishers, agencies. Triggers on: SEO, audit, schema, Core Web Vitals, sitemap, E-E-A-T, AI Overviews, GEO, technical SEO, content quality, page speed, structured 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。

Grounds version-sensitive engineering decisions in authoritative current sources by detecting the installed stack, retrieving official documentation or source, reconciling conflicts, and recording citations and confidence. Use for framework APIs, dependency behavior, standards, compatibility, migrations, or technical recommendations that may have changed. Not for stable project-local logic or broad product 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。

Creates an Architecture Decision Record (ADR) documenting a significant technical decision, its context, alternatives considered, and consequences. Every major technical choice should have an ADR.

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。

Convert 2D orthographic wireframe PNG drawings to 3D Blender models exported as glTF/GLB. Use this skill whenever the user provides wireframe images (technical drawings, line drawings, orthographic views, side/front/back panels) and wants to generate a 3D model, mesh, or .glb file. Triggers on phrases like "convert this wireframe to 3D", "make a 3D model from these drawings", "build a model from this wireframe", "generate GLB from these views", or any image-to-3D-mesh request involving line drawings. Make sure to use this skill even if the user does not explicitly say "wireframe" — also covers "orthographic views", "technical drawings", "line drawings of objects", "front and side views". Requires a configured Blender MCP backend (official or ahujasid) and Python with opencv-python, numpy, scipy installed.

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。

Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"

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。

Convert 2D orthographic wireframe PNG drawings to 3D Blender models exported as glTF/GLB. Use this skill whenever the user provides wireframe images (technical drawings, line drawings, orthographic views, side/front/back panels) and wants to generate a 3D model, mesh, or .glb file. Triggers on phrases like "convert this wireframe to 3D", "make a 3D model from these drawings", "build a model from this wireframe", "generate GLB from these views", or any image-to-3D-mesh request involving line drawings. Make sure to use this skill even if the user does not explicitly say "wireframe" — also covers "orthographic views", "technical drawings", "line drawings of objects", "front and side views". Requires the Blender MCP addon to be running (port 9876) and Python with opencv-python, numpy, scipy installed.

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。

Retrieve patent description (specification) data from the Nexscope patent database by patent ID or publication number. Triggered when users mention patent specification, patent full text, patent technical description, patent embodiment details, Nexscope specification data, patent specification, patent full text, technical description, embodiment details, Nexscope, or patent detailed description. Even if the user does not explicitly say "Nexscope," this skill should be triggered whenever they need to view the complete specification/description content of one or more patents.

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。

Retrieve fulltext images (drawings, diagrams, charts) from patent documents by patent ID or publication number. Triggered when users ask about patent images, patent drawings, patent diagrams, patent illustrations, fulltext drawings, patent charts, patent technical drawings, or want to view/download embedded images in patent documents, patent fulltext drawings, patent diagrams, technical drawings, patent images, or Nexscope. Even if the user does not explicitly mention "fulltext drawings," this skill should be triggered whenever their need involves obtaining visual content (drawings, diagrams, charts) from specific patents.

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。

🇺🇸 SEO & GEO Dual-Engine Playbook 2026 — Rank on Google AND get cited by AI search (ChatGPT, Perplexity, Claude, Gemini). Battle-tested from AFFiNE (60k GitHub stars in 24 months) and 150+ AI startup consultations. E-E-A-T writing voice system, keyword funnel strategy, JSON-LD schema templates, comparison page SOP, IndexNow setup, Generative Engine Optimization content patterns. **Optimized for dev tools / OSS / B2B SaaS. 2C products (education, apps, games): see 2c-adaptation guide in references/.** 🇨🇳 SEO & GEO 双引擎增长手册 —— 同时拿下 Google 排名和 AI 搜索引用（ChatGPT、Perplexity、Claude、文心一言）的完整方法论。AFFiNE 60k stars 与 150+ AI 创业公司咨询实战验证。E-E-A-T 写作声音系统、关键词漏斗、JSON-LD 结构化数据、竞品对比页 SOP、IndexNow 推送、生成式引擎优化内容模式。**默认适用于开发者工具 / 开源项目 / B2B SaaS，2C 产品（教育/应用/游戏）请参考 references/2c-adaptation.md。** 🇯🇵 SEO & GEO デュアルエンジングロースプレイブック — Google検索とAI検索（ChatGPT、Perplexity、Claude）の両方で評価される手法。AFFiNE 60k starsと150社以上のAIスタートアップコンサルティングで検証。E-E-A-Tライティング、キーワードファネル、Schema.org構造化データ、比較ページSOP。**デフォルトは開発者ツール／OSS／B2B SaaS向け。2C製品（教育・アプリ・ゲーム）はreferences/2c-adaptation.mdを参照。** 🇰🇷 SEO & GEO 듀얼 엔진 성장 플레이북 — 구글 검색과 AI 검색(ChatGPT, Perplexity, Claude) 양쪽 모두에서 인용되는 방법론. AFFiNE 60k 스타와 150+ AI 스타트업 컨설팅으로 검증. E-E-A-T 글쓰기, 키워드 퍼널, Schema.org 구조화 데이터, 비교 페이지 SOP. **기본값은 개발자 도구/OSS/B2B SaaS용. 2C 제품(교육·앱·게임)은 references/2c-adaptation.md 참조.** Triggers: "SEO" | "GEO" | "Generative Engine Optimization" | "AI search optimization" | "ChatGPT SEO" | "Perplexity SEO" | "Claude SEO" | "search optimization" | "content SEO" | "technical SEO" | "schema markup" | "JSON-LD" | "structured data" | "IndexNow" | "E-E-A-T" | "keyword strategy" | "keyword funnel" | "comparison page" | "programmatic SEO" | "SaaS SEO" | "搜索优化" | "AI 搜索" | "内容 SEO" | "GEO 优化" | "生成式引擎优化"

Write, restructure, classify, and review documentation with the Diataxis framework. Use when the user asks to create, improve, audit, or reorganize documentation of any kind: knowledge bases, help centers, onboarding guides, process docs, manuals, runbooks, product or API docs, tutorials, how-to guides, references, explanations. Also use when the user mentions Diataxis, docs taxonomy, or documentation architecture, or asks why a document feels confusing. Also use for Simplified Technical English (ASD-STE100) or controlled-language rewrites of English technical docs. Not for marketing, legal, sales, press, or fiction writing unless the user wants a Diataxis-style analysis.

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。

Run a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO / Audit SEO menyeluruh (Technical, On-Page, Schema, Sitemap, E-E-A-T, GEO)

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。

Research a specific technology, library, system, protocol, or tool to answer a concrete technical question with source-traceable evidence. Use when current implementation details, version behavior, configuration, compatibility, or authoritative technical facts must be verified rather than recalled. Also use when explicitly asked to incorporate verified findings into an existing skill.

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。

Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the 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。

Quantitative cost measurement for technical research — token injection costs, payload sizes, context window consumption, and file-level counts from actual repo files. Use when a technical-researcher orchestrator needs the cost dimension of adding or changing something: how many tokens will it inject, how big are the artifacts, what is the context window impact? This is NOT blast-radius analysis (which files break) — it covers size, tokens, and performance cost only.

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 whenever the user wants to find, shortlist, vet, or enrich US SEO agencies — technical SEO, on-page/off-page, link-building, content-led SEO, local SEO, ecommerce SEO, B2B SEO, and SEO audits. Triggers on "find me an SEO agency in Texas", "shortlist three technical SEO consultancies for SaaS", "link-building and on-page for our ecommerce store", or "pull contact info for these 8 SEO firm domains", even when described indirectly (organic traffic flat, improve Google rankings, search visibility). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings, third-party listings. Defer to find-marketing-agency when scope spans multiple marketing services beyond SEO. Skip SEM/PPC/paid-search asks, web-dev asks (use find-web-developer), "how do I rank" DIY questions, SEO tool recommendations (Ahrefs, Semrush), in-house SEO hires, non-US firms, individual freelancers.

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 asked to analyze a file, a directory, or the whole codebase to understand structure, architecture, dependencies, complexity, duplication, dead code, or technical debt — e.g. "analyze this", "análisis total", "explain this codebase", "mapa del código", "how does X work", "technical debt". Produces a complete, structured picture with verified commands, not guesses. Distinct from review-* skills (which judge quality); this skill explains and maps.

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。

Validate and improve GitHub Well-Architected Framework (WAF) documentation under the content/ folder for architectural correctness, decision quality, explicit trade-offs, and actionable guidance. Use this when reviewing pull requests, markdown files, or draft content in content/ to ensure recommendations are technically sound, context-aware, and guide readers toward correct architecture and design decisions.

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。

Comprehensive SEO analysis for any website or business type. Performs full site audits, single-page deep analysis, technical SEO checks (crawlability, indexability, Core Web Vitals with INP), schema markup detection/validation/generation, content quality assessment (E-E-A-T framework per Dec 2025 update extending to all competitive queries), image optimization, sitemap analysis, and Generative Engine Optimization (GEO) for AI Overviews, ChatGPT, and Perplexity citations. Analyzes AI crawler accessibility (GPTBot, ClaudeBot, PerplexityBot), llms.txt compliance, brand mention signals, and passage-level citability. Industry detection for SaaS, e-commerce, local business, publishers, agencies. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "page speed", "structured 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。

Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"

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。

Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, or any visual documentation in markdown.

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。

Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.

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。

Structures technical and commercial DD for resource assets with geological review, operational assessment, and regulatory evaluation. Use when conducting resource DD, evaluating technical reports, or assessing operational risk.

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。

Monitors leveraged loan market conditions with new issue activity, technical dynamics, and CLO demand analysis. Use when analyzing loan markets, tracking CLO activity, or assessing market technical conditions.

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。

Comprehensive 7-phase SEO optimization workflow covering technical SEO auditing, keyword research strategy, on-page optimization, content SEO and E-E-A-T, structured data implementation, link building, and AI search optimization. Use when auditing search engine visibility, diagnosing ranking issues, implementing schema markup, conducting keyword research, optimizing content for E-E-A-T signals, or adapting for AI-driven search (AI Overviews, SGE).

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。