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Discover and characterize regulatory elements (enhancers, promoters, silencers, insulators, super-enhancers) using ENCODE data and the cCRE catalog. Use when the user wants to find candidate regulatory elements, identify active enhancers in a tissue, map promoter states, classify chromatin states with ChromHMM, identify super-enhancers with ROSE, understand the functional validation hierarchy (CRISPR > MPRA > reporter), or characterize non-coding genomic regions. Covers the full workflow from ENCODE cCRE lookup through chromatin state segmentation to functional validation and enhancer-gene linkage. Use this skill for ANY regulatory element discovery, classification, or characterization task.

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Build comprehensive histone mark maps by aggregating narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is this histone mark present in my tissue?" by combining peak calls from multiple studies into a union peak set with confidence annotations. Handles cross-lab batch effects, broad vs narrow marks, and ENCODE blocklist filtering.

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Build comprehensive chromatin contact maps by aggregating Hi-C loop calls (BEDPE) across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "what regions are in 3D contact in my tissue?" by creating a union catalog of chromatin loops. Handles resolution-aware anchor matching, cross-lab variation, and Hi-C-specific quality metrics.

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Build comprehensive epigenomic profiles for tissues or cell types using ENCODE data. Use when the user wants to characterize chromatin states, assemble histone modification panels, create epigenomic landscapes, run ChromHMM segmentation, identify super-enhancers or bivalent domains, profile regulatory elements across a biosample, or understand epigenetic regulation in a specific biological context. Covers histone marks, chromatin accessibility, TF binding, transcription, DNA methylation, and 3D genome structure.

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Use ENCODE functional genomics data for disease mechanism research. Use when the user wants to connect GWAS variants to regulatory elements, annotate disease-associated loci with functional data, identify therapeutic targets from epigenomic data, build disease regulatory models, cross-reference with clinical trials and drug databases, or conduct any disease-focused, pathology-driven, or clinical variant interpretation workflow. Covers the full pipeline from disease-tissue mapping through GWAS variant annotation, heritability enrichment, cancer epigenomics, drug target identification, and clinical trial cross-referencing. Integrates ENCODE with Open Targets, PubMed, ClinicalTrials.gov, and bioRxiv.

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Install bioinformatics tools for ENCODE data analysis. Covers CLI tools (BWA, STAR, samtools, MACS2), R/Bioconductor packages (DESeq2, Seurat, ChIPseeker), Python packages (Scanpy, deeptools), and Nextflow pipeline infrastructure. Generates conda environments, R install scripts, and Python requirements. Use when the user needs to set up a bioinformatics workstation, install tools for a specific assay, create reproducible environments, or troubleshoot dependency issues. Trigger on: install tools, set up environment, conda create, bioinformatics setup, install R packages, install Bioconductor, install pipeline tools.

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Multi-agent review resolution with trust-but-verify methodology. Accepts a PR number/URL or a local code-review report file. Extracts review comments, verifies each with parallel agents using confidence scoring (0-100), filters false positives, presents a triage report for approval, then applies fixes and replies. Use when user runs /resolve-review, mentions "resolve PR comments", "address review feedback", "fix PR suggestions", "handle review comments", or "resolve review findings".

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Analyze existing XML sitemaps or generate new ones with GSC indexing cross-reference. Validates format, URLs, and structure against actual indexing status. Use when user says "sitemap", "generate sitemap", "sitemap issues", "XML sitemap", or "sitemap indexing".

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Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

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Technical SEO audit across 8 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, and JavaScript rendering. Enhanced with live GSC (indexing status, crawl data) and Ahrefs (backlink profile) data when MCPs are available. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

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Deploy and manage serverless applications on Volcengine veFaaS. Use when the user wants to deploy web apps, manage functions (pull code, upload and deploy), configure environment variables, inspect veFaaS projects, troubleshoot vefaas CLI/auth/framework issues, or work with veFaaS services.

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项目规范问题自动修复 Skill。当用户指出项目内的规范偏差时，自动分类问题类型，路由到对应角色Skill执行修复，并通过verifier验证修复效果。类比产品侧「问题追踪+修复」的完整闭环，是项目内规范问题的「接收→分类→执行→验证」一体化机制。触发词：「这里有个规范问题」「这不符合规范」「规范偏差」「按规范修复这里」「这里违反了规范」「规范不对」「帮我修复规范问题」。注意：与 issue-tracker 的区别——后者只记录不执行；本 Skill 记录并自动路由执行。

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项目待办管理器（两种模式）。【收集模式】接收任意混合输入 → 解析追加到「项目待办.md」文档，不立即执行；【处理模式】读取文档 → 前置决策收集 → 按优先级逐条路由执行 → 更新状态 → 批次报告。触发词：【收集】「有几个问题先记到待办」「加到项目待办」「先存到待办文档」「记录这些待办」；【处理】「处理项目待办」「按待办文档逐条修复」「开始处理待办文档」。⚠️ 触发词必须含「待办」关键词才激活，避免与 issue-tracker / bug-fix-loop 混淆。

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用户报告问题时的结构化拆解与追踪。将一个问题拆解为「产品设计类」和「技术实现类」，分别记录到对应的追踪文件，确保产品经理和技术架构师下次激活时能感知到未解决问题。触发词：「有个问题」「发现了bug」「这里不对」「用不了」「为什么会」「有个bug」。

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Generate comprehensive OpenSpec specifications directly from the current project state. Use when the user wants to create or populate main specs by analyzing existing code, documentation, AGENTS.md, GitHub issues, and pull requests — without going through the change/proposal workflow. Ideal for bootstrapping specs on a project that already has working code but no specs yet, or for refreshing specs to match the current implementation.

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Security audit of a codebase — web apps, APIs, services, CLI tools, libraries, daemons, and more. Use when asked to find security bugs, do a security review, audit for vulnerabilities, or pen-test the code. Focuses on exploitable issues with real impact, not theoretical concerns or industry-standard behavior.

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Use this whenever a downstream Vue project needs to absorb upstream Devkit Vue changes — triggers on "update stack", "sync with devkit", "merge upstream", "pull stack updates", "resolve stack conflicts". Two-phase: ISO merge (stack modules stay byte-identical to upstream) then project alignment (apply MIGRATIONS.md, diff project modules vs `tasks` reference, /verify). Stack-code failures get an issue on `pierreb-devkit/Vue`.

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Run this after every code change in this Vue project, before committing, before opening a PR, or whenever the user says "verify", "check", "lint", "run tests", "build", "audit". Diff audit (router guards, store boundaries, UX, /ui consistency, error handling) → lint → tests + coverage gate → build. Coverage drops → add tests, never lower thresholds. Triggers on "is this ready to commit?", "any issues?", "tests passing?".

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Use this whenever the user asks to "open a PR", "ship this", "create the pull request", "make a PR", or once a Vue feature/fix is verified and ready to push. Full lifecycle: branch → commit (commitizen) → issue → draft PR → CI → ready → autonomous monitor loop (fix comments, resolve threads, iterate until CI green + zero unresolved threads). `--perfect` adds a CodeRabbit convergence loop on top. Never works on `main`/`master`, never uses `--no-verify`.

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Detect project linting and validation tools, build an execution pipeline, run all tools to zero errors, and fix issues using an atomic fix protocol. Auto-detects Makefile targets, package.json scripts, Go tools, Python tools, and other common linters. Use when fixing linting errors, running validation pipelines, or ensuring code quality before committing.

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Generate a PR_MESSAGE.md file from session context using GitHub CLI. Detects related issues via branch-keyword search, writes a structured PR description with commit subject, summary, test plan, and changelog. Validates with commitlint and markdownlint. Use when preparing a pull request on GitHub.

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Strategic roadmap management for GitHub repositories. Syncs ROADMAP.md with GitHub Issues and labels, bootstraps roadmap files from scratch, runs brainstorming sessions with boundary checking, and provides quick status summaries. Use when managing project planning, syncing roadmap state, or exploring feature ideas.

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Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.

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Full-stack app pipeline — build, test, review, and deploy across one or ALL repos. Scans CLAUDE.md, MEMORY.md, TODOs, open PRs, and issues for shippable work. Supports 'ship all' for multi-repo. Use when: 'build and ship', 'ship it', 'ship all', 'deploy everything', 'full pipeline', 'what needs shipping', 'end to end'.

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。