254 件 ・ 関連度順
概要と使いどころ
Rapidly maps the evidence landscape around a medical topic by organizing major research streams, target populations, endpoints, methods, evidence density, and thin areas. Use this skill BEFORE medical-research-gap-finder — it provides the structured landscape that makes formal gap analysis more rigorous. Do not use for formal gap identification, study design, or protocol planning directly.
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 competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy 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。
Analyze competitors and create competitive landscape documentation with feature matrices, positioning maps, and strategic recommendations. Use when asked to analyze competitors, create competitive analysis, compare features with competitors, build a competitive landscape, track competitive positioning, or prepare sales battlecard inputs. Produces structured competitor profiles, feature comparison matrix, win/loss analysis, and prioritised strategic recommendations. For a one-off teardown of a single rival use competitor-teardown; for a recurring market briefing use competitive-intelligence-monitor.
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。
Monitor competitor signals and surface strategic implications for your roadmap. Use when asked to monitor competitors, track the competitive landscape, produce a competitive briefing, or understand what has changed in the market this week or month. Produces a structured intelligence brief with high/medium/low priority signals, roadmap implications, and a strategic landscape summary. For a single competitor announcement use competitor-signal-tracker; for a one-off deep dive use competitor-teardown.
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。
Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.
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。
Analyze current trends and challenges in Japanese NLP for a topic. Surveys the existing awesome-japanese-nlp-resources dataset and augments it with up-to-the-minute web research to produce a combined trend + issue report. Use only when the user explicitly wants a trend/landscape report, a challenges/limitations report, or a general research overview of a Japanese NLP topic (this combines the bundled dataset with live web research). Trigger phrases include '日本語LLMの最新トレンド', '〜の動向をまとめて', '最近の日本語NLPの流れ', '日本語LLMの課題', '〜の問題点・限界', '未解決の論点', 'trend report on Japanese embeddings', 'latest Japanese speech models', 'challenges in Japanese NER', 'limitations of Japanese embeddings'. For a simple lookup use the search skill; this one runs web research.
Use when building or fixing an Unreal Engine 5 level or open world: World Partition, OFPA, Data Layers, Level Instances, Packed Level Actors, HLOD, landscape size, heightmap import or clipping, edit layers, terrain material rules, foliage and grass, a PCG forest or rock scatter, runtime GPU grass, Nanite and tessellation choices, modular kits, a river or village, streaming pop-in, cells not loading, landscape black spots, "PCG shows nothing in the editor", or a world too heavy to hand to lighting.
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 competitive narrative landscape and score unclaimed positioning gaps. "find us a differentiated position"
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 A-share sector and industry landscape reports — market size, competitive positioning, policy environment, key A-share players, trading multiples, and thematic trends. Adapted from the original sector-overview skill for Chinese market structure and terminology. Triggers on "A股行业分析", "行业研究", "板块分析", "sector overview China", "A-share sector deep dive", "白酒/半导体/新能源 行业分析", or "[industry] landscape China".
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。
Competitive landscape analysis for A-share companies and Chinese industries. Maps competitors, compares positioning, and assesses relative strengths. Adapted from the original competitive-analysis skill for Chinese market context. Triggers on "A股竞争格局", "行业竞争分析", "competitive landscape China", "competitive analysis A-share", or "[company] competitors China".
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。
Analyze how competitors present their brand — identity, messaging, positioning, voice, and visual style — to find gaps and opportunities. Use when the user says "competitor brand analysis", "analyze competitor brands", "how do competitors position themselves", "competitor messaging", "competitor identity", "what are competitors saying", "benchmark competitors", "competitive brand landscape", "how do we compare to competitors", "competitive audit", or wants to understand the brand landscape before defining their own position.
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。
Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning. Use when the user asks to analyze competitors, benchmark against rivals, understand competitive landscape, find competitor weaknesses, or build a competitive matrix. Trigger phrases include "competitor analysis", "competitive analysis", "who are my competitors", "competitor research", "competitive landscape", "benchmark competitors", "competitor ads", "competitor SEO", "competitor pricing", "SWOT analysis", "competitive matrix".
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。
Resizes, scales, and adjusts video resolution and dimensions using GPU-accelerated NVENC encoding via Volcengine LAS. Video resizing, video scaling, video upscaling, and video downscaling — change video resolution, enlarge or shrink video dimensions, and adjust video size for different platforms and screens. Video compression by reducing resolution and video transcoding and re-encoding with specific dimension constraints. Supports flexible min/max width and height ranges with aspect ratio preservation strategies (increase, decrease, or disable), including landscape to portrait conversion. Async submit-poll workflow with batch support. Use this skill when the user wants to resize or scale video resolution (upscale/downscale), change video dimensions for different platforms, compress videos by reducing resolution, transcode/re-encode videos with GPU NVENC, adjust aspect ratio including landscape-to-portrait conversion, adapt videos for mobile/web/social media, or batch process multiple videos.
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。
Structured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning
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。
Turn Chinese classical poems and ci into coherent vertical Chinese-art videos with poem-driven scene grouping, GPT ImageGen stills, Docker-only Gemini I2V, retained model-generated ambience, Gemini sparkle-watermark cleanup, brush-calligraphy captions revealed character by character, optional local BGM mixing, stitching, and final-frame QA. Supports verse-driven variation across ink landscape, gongbi bird-and-flower, colored figure-and-horse painting, blue-green landscape, xuan paper, silk, and related Chinese visual languages. Use when users ask for 古诗词动态视频、诗词逐句或两句一景、国风视频、毛笔字逐字出现、整首诗拼接成片，or want the established 月落乌啼霜满天 workflow applied to another poem.
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。
Framework for competitive landscape analysis across any industry. Use when creating competitor analysis, market positioning assessments, investment memos, strategic reviews, or any analysis requiring systematic evaluation of competitive dynamics. Triggers include requests for competitive landscape decks, peer comparisons, market structure analysis, strategic positioning assessments, and investment recommendations.
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 big picture around a topic or software repository by identifying its boundaries, layers, actors, components, relationships, flows, history, fault lines, and open questions, then explain how the pieces fit together and where to look next. Use when a user asks to understand a whole field, domain, technology, ecosystem, industry, codebase, architecture, unfamiliar repo, or phrases such as "give me the big picture", "map the landscape", "how does this all fit together?", "help me get oriented", or "what am I missing?"
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 any industry's competitive landscape using company databases, academic research, news coverage, LinkedIn activity, and job market signals. Produces industry overviews with key players, market segments, growth indicators, and emerging disruptors.
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 competitor analysis, competitive intelligence, and comparison page creation. Use when analyzing competitive landscape, creating competitor comparison pages (alternative pages, vs pages, competitor A vs B pages), performing market research, building SWOT analysis, creating feature matrices, pricing comparisons, competitor teardowns, battle cards, or positioning maps. Covers research workflows, SEO-optimized comparison content, data-grounded reports with citations, 7-layer analysis framework, review mining, and sales enablement. Triggers include competitor analysis, competitive analysis, competitor teardown, vs page, alternative page, competitor comparison, market research, competitive intelligence, SWOT analysis, battle card, competitor pricing, market landscape, feature comparison, positioning map.
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 market research and analysis skill. Use when sizing markets, conducting competitive analysis, generating professional market research reports, analyzing consumer behavior, or identifying market opportunities. Activates for: market research, market analysis, market report, TAM SAM SOM, market sizing, industry analysis, market landscape, competitive landscape, market trends, consumer research, Porter's Five Forces, PESTLE, SWOT, BCG Matrix, McKinsey-style report, consulting report, market opportunity, industry report, due diligence, M&A analysis, GTM market analysis, product-market fit validation.
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。
Maps competitive dynamics with market positioning, feature comparison, funding histories, and differentiation assessment. Use when analyzing startup competition, mapping market landscapes, or identifying competitive threats.
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。
Maps a startup's competitive landscape, scores moat strength across 6+ dimensions, and writes an investor-ready competition narrative with a positioning map. Use when the user asks for a competitive landscape, moat analysis, or positioning review and gives enough to work from: a deck, a list of competitors, or a clearly named startup. A full run takes about 30–40 minutes and searches the web, so for a passing question such as 'who are my competitors?' or 'is that a real moat?', answer briefly in chat and offer the analysis instead of starting it. When it runs, the competitor set and moat scores are checked adversarially, never recalled from memory.
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。
5つの専門エージェントがディスカッション型で競合のビジネスモデル・機能・価格・弱点を網羅的に分析し、 差別化ポイントと参入戦略を導出するスキル。 エージェント同士が対話・批判し合いながら調査し、ca-data-critic がライブモデレーターとして矛盾を検出・収束を判定する。 Phase 1 で競合プロファイル・レビュー・機能をディスカッション型で調査し、 Phase 2 でポジショニング戦略家が統合。 Gate 1（中間合意形成）→ Gate 2（最終検証 + Independent Validation + Devil's Advocate）の2段階ゲートで品質を担保。 Use when: 競合を分析したい、差別化ポイントを見つけたい、 市場のプレイヤーを調べたい、ポジショニングを考えたい。 Triggers: "競合分析", "competitive analysis", "競合調査", "差別化", "ポジショニング", "competitor", "競合", "市場プレイヤー", "ライバル調査", "competitive landscape"
Map who is winning an SEO market with measured data — recurring SERP domains, organic footprints, winning content themes, backlink authority, and the gaps worth attacking. Use this skill for market-level questions ("who ranks for X", "how competitive is this space", "where are the SEO openings") before committing to keyword targets or content themes. For one named competitor, use openseo-competitor-analysis instead. Triggers: "competitive landscape seo", "who ranks for", "seo market map", "how competitive is", "serp competitors".
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。