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概要と使いどころ
Evaluates signal half-life, turnover implications, and capacity constraints for systematic alpha factors. Use when analyzing signal persistence, evaluating factor decay, or estimating strategy capacity.
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Evaluates cornerstone investment commitments with allocation guarantees, lock-up terms, and signaling value assessment. Use when structuring cornerstone tranches, analyzing anchor investors, or evaluating demand signals.
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。
Design and build cinematic websites, interactive portfolios, product stories, and real-time 3D experiences with subject-specific art direction and scroll choreography. Use for new builds, redesigns, motion improvements, scroll audits, or storyboards in standalone HTML and existing apps; includes responsive, reduced-motion, and static fallbacks. Not for ordinary dashboards or unrelated animation.
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。
Hunt Server-Side Template Injection (SSTI) in Jinja2, Twig, Freemarker, Velocity, Smarty, ERB, Handlebars, Mustache, and Spring (SpEL). Use when input is reflected in a way that suggests template rendering — error pages, email templates, PDF generators, dynamic content systems.
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。
论文检索子 skill。通过 OpenAlex API（默认）、arXiv、Semantic Scholar、CrossRef 四个免费源聚合搜索学术文献，返回结构化论文元信息（含 DOI / 摘要 / 引用数）。 默认零配置；可选 EZMM_OPENALEX_EMAIL / EZMM_S2_API_KEY 提升配额。
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。
Systematically audit and remediate accessibility issues in UI, focusing on keyboard navigation, screen reader support, color contrast, semantic HTML, ARIA usage, and motion sensitivity. Use when the user wants to improve accessibility, make a component accessible, fix WCAG violations, add keyboard support, or ensure screen reader compatibility.
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。
Build or refine UI color systems, warmth, semantic color, and color-based hierarchy in designs that are too gray, monochromatic, or missing color meaning. Use when the user mentions dull colors, gray UI, missing warmth, weak semantic color, or a need for stronger color hierarchy.
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。
Creates JSON Schema validation files for skills, agents, hooks, workflows, and data structures. Ensures type safety and input validation across the framework.
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。
Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.
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。
Applies general rules for Convex development, emphasizing schema design, validator usage, index-first query patterns, function registration, and correct handling of system fields.
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。
Rules for Drizzle ORM schema design, query patterns, migration workflows, and relational query usage. Ensures type-safe, production-ready database interactions.
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。
Semantic code search using Phase 1 vector embeddings and Phase 2 hybrid search.
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。
Audits websites for AI search visibility (GEO/SEO) and generates deployable artifacts (llms.txt, schema JSON-LD, robots.txt). 7-dimension scorecard tailored by site type and size, grounded in Princeton KDD 2024, Toronto 2025, and ICLR 2026 research. This skill should be used when optimizing for ChatGPT, Perplexity, Google AI Overviews, or other AI search engines. Also triggered by queries about AI search optimization, generative engine optimization, llms.txt, AI crawler configuration, schema markup for AI, citation optimization, or Google AI Mode.
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。
Source pre-2016 cinema with gothic/occult sensibility, literary texture, and historical grandeur — build watchlists, curate Criterion/MUBI picks. Uses Perplexity for film discourse, Exa for web search, Firecrawl for scraping. Triggers on film recommendations, watchlist, gothic cinema, occult film, arthouse, pre-2016 movies.
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 images with precision using ImageMagick 7, sips, transparent-background, and Pillow — with intelligent routing to AI semantic editing (Gemini/nano-banana-pro) for content-aware operations. Covers cropping, resizing, compositing, annotating, format conversion, color adjustment, background removal, batch processing, and montage creation. Triggers on image editing, crop, resize, composite, annotate, remove background, format conversion.
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。
Coordinate SEO, LLM-readable site architecture, UX, content, monitoring, security, and external authority work as a task-plan-driven sequence. Use this skill when the user asks to plan, execute, validate, or route multi-skill website growth work; asks what to do next across semantic core, URL structure, internal linking, schema, llms.txt, UX journeys, analytics, citation monitoring, or white-hat link placement; or wants a central architect that preserves evidence, alarms, handoffs, and tests.
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 SEO and LLM-readability claims against live HTML, local fixtures, and generated artifacts. Use this skill when the user asks to prove whether title, meta description, canonical, hreflang, JSON-LD, NewsArticle.image, OpenGraph, Twitter cards, RSS autodiscovery, robots.txt, llms.txt, sitemap, news-sitemap, crawler access, or performance evidence is actually present, and when subjective audits must become timestamped pass/fail reports.
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。
Specialized research and analysis prompt methodology for Claude. Provides 11 tested approaches (3 identity, 4 reasoning, 4 output) for data analysis, policy research, systematic evidence review, investigative research, and research-specific deliverables. Use when building prompts for quantitative data interpretation, evidence-based policy recommendations, literature reviews, causal analysis, hypothesis-driven investigation, or briefing documents. Trigger on: "prompt for data analysis," "research prompt," "policy brief prompt," "literature review prompt," "prompt for investigating," "systematic review prompt," "build a prompt for evidence synthesis," "causal analysis prompt," "briefing document prompt." Also use when user describes a research or analytical task and needs a structured Claude prompt for it. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available) or auditing Claude Projects (use rootnode-project-audit if available).
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。
Prepare an organisation for regulatory inspection by assessing readiness against agency-specific focus areas (FDA, EMA, MHRA). Covers warning letter and 483 theme analysis, mock inspection protocols, document bundle preparation, inspection logistics, and response template creation. Use when a regulatory inspection has been announced or is anticipated, when a periodic self-assessment is due, when new systems have been implemented since the last inspection, or after a significant audit finding that may attract regulatory attention.
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。
AI intuitive exploration for approaching unknown codebases, problems, or systems without preconceptions. Adapts the Coordinate Remote Viewing protocol to AI investigation: cooldown (clear assumptions), staged data gathering (raw signals → dimensional → analytical), AOL management (separating observations from premature labels), and structured review. Use when investigating an unfamiliar codebase with unknown architecture, debugging a problem where premature hypotheses could mislead, exploring a domain with limited context, or when previous attempts have been led astray by assumptions and "beginner's mind" would be more productive.
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。
Field identification of minerals and ores using hardness, streak, luster, cleavage, crystal habit, and simple chemical tests. Covers the systematic elimination methodology, Mohs scale application, and common ore indicators for precious metals, gemstones, and industrial minerals. Use when encountering an unknown rock or mineral specimen, when prospecting and assessing whether a site shows valuable mineral indicators, when distinguishing ore-bearing rock from barren rock in the field, or when building geological literacy through systematic observation.
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。
Derive a theoretical result step-by-step from first principles or established theorems, with every step explicitly justified and special cases checked. Use when deriving a formula or theorem from first principles, proving a mathematical statement by logical deduction, re-deriving a textbook result for verification or adaptation, extending a known result to a more general setting, or producing a self-contained derivation for a paper or thesis.
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。
Apply semantic versioning (SemVer 2.0.0) to determine the correct version bump based on change analysis. Covers major/minor/patch classification, pre-release identifiers, build metadata, and breaking change detection. Use when preparing a new release to determine the correct version number, after merging changes before tagging, evaluating whether a change constitutes a breaking change, adding pre-release identifiers, or resolving disagreement about what version bump is appropriate.
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。