3,722 件 ・ 関連度順
概要と使いどころ
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversion analysis, or when user mentions funnels, conversion rates, or user flow 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。
Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak 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。
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
The 100th skill! Your intelligent guide to all 99 other skills. Recommends the perfect skill for any task, creates skill combinations, and helps you discover capabilities you didn't know you had.
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。
Ad Performance Auditor — analyze existing ad campaigns and identify optimization opportunities
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。
Beanstalk integration. Manage Persons, Organizations, Deals, Leads, Activities, Notes and more. Use when the user wants to interact with Beanstalk 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。
Arive integration. Manage Leads, Persons, Organizations, Deals, Projects, Activities and more. Use when the user wants to interact with Arive 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。
Ambivo integration. Manage Organizations, Pipelines, Users, Filters, Activities, Notes and more. Use when the user wants to interact with Ambivo 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。
Agile CRM integration. Manage Persons, Organizations, Deals, Leads, Activities, Notes and more. Use when the user wants to interact with Agile CRM 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。
8x8 integration. Manage Persons, Organizations, Deals, Leads, Activities, Notes and more. Use when the user wants to interact with 8x8 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。
Act! 365 integration. Manage Contacts, Groups, Opportunities, Tasks, Users. Use when the user wants to interact with Act! 365 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。
Turn ONE topic, talking-head video, or photo into a finished Vox-style paper-collage explainer / ad video on the MuAPI platform (api.muapi.ai) + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Three input modalities: a topic (B-roll), a talking-head video (A-roll mode), or a single photo of a person/product anchored into the collage (C-roll 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。
Fix empty results when paginating Wayback Machine CDX API with wildcard URL queries. Use when: (1) CDX query with url=foo/* and page=0 returns empty/0 bytes but works without page parameter, (2) CDX pagination returns no data for wildcard prefix searches, (3) Need to paginate large CDX result sets using wildcard URL matching. Covers showResumeKey, offset, and page parameter incompatibilities.
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 you need to display chronological events and activities.
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。
Automatically migrate Spring MVC applications to Spring Boot. Use when you need to modernize a Spring MVC project to Spring Boot while preserving functionality. The skill analyzes the codebase, updates build configuration (Maven/Gradle), migrates annotations, converts XML configuration to Java/properties, updates controllers and tests, and creates the Spring Boot main application class. Creates git commits for each migration phase and generates a comprehensive summary. Supports both Maven and Gradle projects.
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。
Automatically simplify and minimize TLA+ specifications by reducing redundant state variables, merging equivalent actions, and minimizing invariants while preserving specified properties. Use when working with TLA+ specifications that need optimization, simplification, or reduction. Triggers when users ask to minimize, reduce, simplify, or optimize TLA+ specs, or when they want to remove redundancy from formal specifications while maintaining semantic equivalence.
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。
Automatically generate TLA+ specifications from source code (C/C++, Python) for formal verification of distributed systems. Use when users need to: (1) Generate TLA+ specs from program implementations, (2) Model distributed systems, consensus protocols, or concurrent algorithms, (3) Extract state variables, actions, and invariants from code, (4) Create formal specifications for model checking with TLC, (5) Verify safety and liveness properties of distributed systems. Particularly effective for message-passing systems, replication protocols, consensus algorithms, and distributed transactions.
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。
Scan repositories for newly disclosed CVEs in dependencies after a specific cutoff date. Takes a repository path, cutoff date (YYYY-MM-DD), and optional parameters for transitive dependencies. Parses dependency manifests (package.json, pom.xml, requirements.txt, go.mod, Cargo.toml) and lockfiles to extract exact versions. Queries vulnerability databases (OSV.dev, NVD, GitHub Advisory) to identify CVEs disclosed strictly after the cutoff date. Distinguishes between newly disclosed CVEs and previously known CVEs. Use when: (1) Performing security audits to find new vulnerabilities since last review, (2) Checking if new CVEs affect a historical codebase version, (3) Generating compliance reports showing vulnerability status at specific dates, (4) Tracking security posture changes over time. Supports npm, Maven, pip, Go modules, Cargo, and other major ecosystems.
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 vulnerable code to identify underlying root causes such as violated assumptions, incorrect invariants, missing validation checks, or unsafe component interactions. Use when investigating security vulnerabilities, CVEs, exploit code, or security audit findings. Infers why the vulnerability exists beyond surface symptoms, identifies systemic issues, and explains the chain of failures that enable exploitation.
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。
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.
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。
Proposes secure remediation strategies for detected security vulnerabilities including buffer overflows, injection risks, insecure deserialization, improper authentication, and unsafe cryptographic usage. Provides recommended security checks, safer API alternatives, design-level changes, code examples, trade-off analysis, and prioritized remediation plans. Does NOT automatically modify code unless explicitly requested.
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。
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
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.
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。
Extract and summarize core features, constraints, and priorities from requirement documents. Use when analyzing PRDs, RFCs, business requirements, user stories, epics, or any requirement documentation to identify must-have features, technical constraints, priority levels (P0/P1/P2/MoSCoW), and key decision points. Triggers when users ask to summarize, analyze, extract, or understand requirements from documents.
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。