Search the web and ingest results as wiki pages
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →Search the web and ingest results as wiki pages
Creates procedural and organic shapes in Minecraft using VibeCraft MCP tools. Use when building spheres, domes, cylinders, pyramids, torus, arches, curves, spirals, organic shapes, statues, or any complex geometry that requires procedural generation.
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方案设计阶段详细规则；进入方案设计时读取；包含方案构思、任务拆解、风险评估、方案包创建
用于生成中国软件著作权申请材料的完整工具包。支持从项目代码、文档等自动提取信息，生成软件著作权登记申请表、源代码文档（前后各30页）、用户手册和设计说明书，并自动转换为PDF文件。适用于微信小程序、Web应用、移动App、桌面应用等各类软件项目。当用户需要申请中国软件著作权时使用此skill。
Transform podcast transcripts into multiple content assets—blog posts, social snippets, newsletters, and SEO-optimized landing pages—using systematic repurposing workflows. Use when: Maximizing ROI from podcast episodes; Creating blog content from audio/video; Generating social media posts from long-form content; Building newsletter content from transcripts; Extracting quotes and highlights for promotion
Create marketing visualizations from data. Use when: creating charts for reports; visualizing campaign performance; generating dashboards; presenting data insights; exporting charts for presentations
Generate PDF/HTML reports from templates and data. Use when: creating client reports; generating weekly summaries; producing marketing performance reports; automating recurring reports
Transcribe audio and video files to text using OpenAI Whisper. Use when: converting podcasts to blog posts; creating video subtitles; extracting quotes from interviews; repurposing video content to text; building searchable audio archives
> Write copy that sells NOW using Dan Kennedy's "No B.S." direct response marketing principles
Master email marketing from subject lines to sequences. Templates for welcome emails, nurture campaigns, sales emails, and newsletters that get opened, read, and clicked. Use when: Writing email subject lines that get opens; Creating welcome email sequences; Building nurture and sales sequences; Writing newsletters that engage; Re-engagement and win-back campaigns
Write high-converting direct response sales letters using the proven methodologies of Gary Halbert (The Boron Letters) and Dan Kennedy (The Ultimate Sales Letter)—master the art of persuasive long-form copy that turns readers into buyers. Use when: **Write a long-form sales letter** for a product or service; **Create direct mail pieces** that generate response; **Write landing page copy** in sales letter format; **Craft email sequences** with direct response principles; **Develop VSL scripts*...
Coordinate crisis response through structured playbooks, communication templates, and team orchestration
Create winning RFP/RFI responses by analyzing requirements, structuring compliant proposals, and crafting compelling win themes
Generate JSON-LD structured data for SEO. Use when: adding schema markup to pages; creating organization schema; generating product schema; validating existing schema; rich snippet optimization
Generate XML sitemaps for SEO. Use when: creating sitemap for new site; updating sitemap after changes; generating sitemap from URLs list; validating existing sitemap
Generate high-quality LinkedIn posts for GEO thought leadership. Use when asked to write LinkedIn content, create social media posts, or generate content about SEO/GEO topics.
Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health.
Orchestrate iOS/macOS app scaffolding and optional skill adoption for existing projects. Use when users want a guided wizard that can scaffold with XcodeGen and optionally install xcode-makefiles and simple-tasks.
Generate a structured, actionable launch checklist tailored to the user's app,
Write a description summarizing implemented work. Generates PR/MR descriptions from completed changes.
An intelligent documentation system that analyzes codebases and generates
monte-carlo-prevent
Generate comprehensive ontological knowledge graphs in [[wikilinks]] syntax for InfraNodus visualization. Use when the user requests to create an ontology, extract entities and relationships from text, or generate knowledge graph structures. Handles both topic-based ontology generation and entity extraction from existing text. Output is formatted for direct paste into InfraNodus.com for network visualization and AI-powered gap analysis.
Generate high-CTR YouTube thumbnails, titles, and video scripts optimized for virality. Use when the user asks to create YouTube video titles, thumbnail text/concepts, video scripts, optimize existing titles for CTR, analyze why a video isn't performing, or needs help making content more clickable. Covers thumbnail wording, title copywriting, video script structuring (Pattern Interrupt → Hook → Framing → Curiosity Loop → Escalation → Payoff → Relevance Bridge → Loop Reopen), and YouTube algorithm optimization.
Reddit & X/Twitter auto-reply bot for ecommerce/SaaS growth. Finds relevant posts about AI customer service, Amazon FBA, Shopify — posts genuine AI-generated replies mentioning your product. Includes Reddit account warmup (karma building) and lead tracking. Triggers: social reply bot, reddit auto reply, twitter auto reply, x auto reply, social media bot, amazon seller engagement, ecommerce social engagement, reddit warmup, karma building, warmup reddit, social leads, potential customers
- [Overview](#overview)
Performs abstract interpretation to produce summarized execution traces and high-level program behavior representations. Highlights key control flow paths, variable relationships, loop invariants, function summaries, and potential runtime states using abstract domains (intervals, signs, nullness, etc.). Use when analyzing program behavior, understanding execution paths, computing loop invariants, tracking variable ranges, detecting potential runtime errors, or generating program summaries without concrete execution.
Summarizes the complete lifecycle of a bug across code versions, tracking its introduction, detection, fixing attempts, and regression history. Use when users need to: (1) Understand how a bug evolved over time, (2) Trace when and how a bug was introduced, (3) Analyze fix attempts and their effectiveness, (4) Identify regression patterns, (5) Generate bug lifecycle reports for documentation or post-mortems. Takes a repository, bug identifier, and version history as input.
Translate C or C++ programs into equivalent Lean4 code, preserving program semantics and ensuring the generated code is well-typed, executable, and can run successfully. Use when the user asks to convert C/C++ code to Lean4, port C/C++ programs to Lean4, translate imperative code to functional Lean4, or create Lean4 versions of C/C++ algorithms.
Generate meaningful, maintainable comments and documentation for your code.
Search code repositories for code related to a given code snippet, ranking results by call chain similarity, textual similarity, and functional similarity. Use when finding related code, locating similar implementations, discovering code dependencies, or identifying code that performs similar operations. Outputs ranked file lists with matching code snippets and relevance scores.
Generate configuration files for applications, services, and infrastructure. Use when: (1) Setting up new projects (package.json, requirements.txt, tsconfig.json), (2) Creating Docker or Kubernetes configurations, (3) Configuring CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI), (4) Setting up web servers (Nginx, Apache), (5) Defining infrastructure as code (Terraform, CloudFormation), (6) Generating linter/formatter configs (ESLint, Prettier, Black). Provides templates and custom-generated configs for diverse tech stacks.
Generate Dockerfiles, Docker Compose configurations, and Kubernetes manifests for containerizing applications. Use when: (1) Creating Dockerfiles for Node.js, Python, Java, Go, or other applications, (2) Setting up multi-service environments with Docker Compose, (3) Generating Kubernetes deployments, services, and ingress configurations, (4) Optimizing container images for production, (5) Implementing containerization best practices. Provides both ready-to-use templates and custom-generated configurations based on project requirements.
Generate abstract Control Flow Graph (CFG) representations of programs showing loops, branches, and function calls for static analysis or verification. Use when users need to: (1) Visualize program control flow structure, (2) Generate CFGs for static analysis tools, (3) Create control flow abstractions for formal verification, (4) Analyze program paths and reachability, (5) Document program structure. Supports both function-level (intraprocedural) and program-level (interprocedural) analysis with multiple output formats (textual, DOT/Graphviz, JSON).
Translate C/C++ programs to equivalent Dafny code while preserving semantics and ensuring verification. Use when users ask to convert, translate, or port C/C++ code to Dafny, or when they need to formally verify C/C++ algorithms using Dafny's verification capabilities. Handles functions, structs, pointers, arrays, memory management, and ensures the generated Dafny code is well-typed, executable, verifiable, and can successfully run.
Analyze detected vulnerabilities to assess realistic exploitability by examining control flow, input sources, sanitization logic, and execution context. Use when users need to: (1) Determine if a vulnerability is actually exploitable in practice, (2) Assess severity and impact of security issues, (3) Prioritize vulnerability remediation, (4) Understand attack vectors and exploitation conditions, (5) Generate exploitability reports with proof-of-concept scenarios. Focuses on injection vulnerabilities (SQL, command, XSS, path traversal, LDAP) with detailed analysis of reachability, controllability, sanitization, and impact.
Automatically infer loop invariants for code verification and correctness proofs. Use when analyzing loops to identify properties that hold throughout execution, generating assertions for verification, proving loop correctness, or documenting loop behavior. Supports Python, Java, C/C++, and language-agnostic analysis. Generates invariants as code assertions (assert statements). Triggers when users ask to infer invariants, find loop properties, generate loop assertions, prove loop correctness, or verify loop behavior.
Analyze failed or stuck proofs and propose auxiliary lemmas to help complete the proof in Isabelle/HOL or Coq. Use when encountering proof failures, stuck proof states, unprovable subgoals, or when needing to strengthen induction hypotheses. Identifies missing lemmas, suggests proof strategies, and generates helper lemmas with appropriate statements and proof sketches. Supports inductive proofs, case analysis, rewriting, and complex proof obligations.
Generate structured proof skeletons with tactics, strategies, and intermediate lemmas for theorems in Isabelle/HOL or Coq. Use when users need to: (1) Create proof outlines for theorem statements, (2) Generate proof structure with tactic placeholders, (3) Identify key lemmas needed for a proof, (4) Plan proof strategies (induction, case analysis, forward/backward reasoning), (5) Scaffold proofs with intermediate steps and subgoals, or (6) Convert theorem statements into detailed proof templates. Supports both Isabelle/HOL and Coq equally.
Translate Python programs to equivalent Lean4 code while preserving semantics and ensuring type safety. Use when users ask to convert, translate, or port Python code to Lean4, or when they need to verify Python algorithms using Lean4's theorem proving capabilities. Handles functions, classes, data structures, control flow, and ensures the generated Lean4 code is well-typed, executable, and can successfully run.
Generate comprehensive, user-friendly README.md files for code repositories. Use when creating documentation for new projects, updating existing READMEs, or improving project onboarding. Produces READMEs with project introduction, prerequisites, environment setup, executable usage instructions, and repository structure overview. Supports application projects, libraries, and research codebases.
Creates structured context summaries for continuing work across AI sessions. Use when ending a session to enable seamless continuation in a new session without losing context.
Automatically extract abstract finite-state models in SMV/NuSMV format from source code (C/C++, Java, Python) for formal model checking. Use when users need to: (1) Generate SMV models from program code for verification, (2) Extract state-transition models from protocol implementations, (3) Analyze control flow and data flow to construct formal models, (4) Create models for checking safety and liveness properties, (5) Convert imperative code to declarative state machines. Particularly effective for protocol implementations, concurrent systems, and control logic with clear state transitions.
Interview-based strategic planning for complex software tasks. Conducts structured requirements gathering, gap analysis, and generates detailed work plans before implementation begins.