627 件 ・ 関連度順
概要と使いどころ
PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.
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。
scikit-learn compatible Python toolkit for time series ML: classify, cluster, regress, segment, transform with 30+ algorithms (ROCKET, InceptionTime, KNN-DTW, HIVE-COTE, WEASEL). Handles panel, multivariate, and unequal-length series. Maintained successor to sktime. Alternatives: sktime (larger ecosystem), tslearn (fewer algorithms), catch22 (features only).
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。
Python image processing for microscopy and bioimage analysis. Read/write images, filter (Gaussian, median, LoG), segment (thresholding, watershed, active contours), measure region properties, detect features. SciPy/NumPy ecosystem. Use OpenCV for real-time video; CellPose for DL cell segmentation; napari for visualization.
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。
Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development. Use this skill when building ROS1 nodes, packages, launch files, or debugging ROS1 systems. Trigger whenever the user mentions ROS1, catkin, rospy, roscpp, roslaunch, roscore, rostopic, tf, actionlib, message types, services, or any ROS1-era robotics middleware. Also trigger for migrating ROS1 code to ROS2, maintaining legacy ROS1 systems, or building ROS1-ROS2 bridges. Covers catkin workspaces, nodelets, dynamic reconfigure, pluginlib, and the full ROS1 ecosystem.
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。
Provides integration patterns for LangChain4j with Spring Boot. Configures AI model beans, sets up chat memory with Spring context, integrates RAG pipelines with Spring Data, and handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications, building Java LLM applications with @Bean configuration, or setting up Spring AI patterns.
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。
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
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。
Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.
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。
Audit and safely repair cross-runtime Skill governance: canonical-source ownership, divergent or duplicate projections, exposure scopes and budgets, lifecycle drift, quarantine, and retirement. Use when the user explicitly requests cross-runtime or cross-scope Skill governance; ignore project-local Skill inventory, product/runtime loading or enablement checks, usage statistics, and mentions/traces.
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。
只读统计 Claude/Codex 的 Skill 使用证据并检查 agent 配置健康。仅用于明确的健康检查、配置诊断、使用排行或低使用候选请求；会识别 enabled 插件并单列批量审计读取。不要用于规范源、触发、全局/项目/profile/冷存储、投影或退役治理，改用 skill-ecosystem-doctor。忽略引用日志和相邻任务。
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。
Generate GitHub Actions CI/CD pipeline configurations for automated building and testing of library and package projects. Use when creating or updating CI workflows for npm packages, Python packages, Go modules, Rust crates, or other library projects that need automated build and test pipelines. Includes templates for common package ecosystems with best practices for dependency caching, matrix testing, and artifact publishing.
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 auditing a product, business, or project ecosystem — analyzing data sources, decision loops, bottlenecks, and implementation contours. Triggers on "аудит продукта", "product audit", "data audit", "аудит данных", "аудит бизнеса", "проанализируй экосистему", "аудит систем".
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。
Research WeChat Official Account articles, analyze account profiles, track article performance, and read comments. Covers article discovery, account profiling, engagement statistics, comment analysis, and content strategy research on China's dominant messaging ecosystem.
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。
Search articles, videos, and content within the WeChat ecosystem. Covers cross-content-type search including Official Account articles, video channels, and mini-programs — the gateway to China's largest private-traffic platform.
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。
Research podcasts, episodes, and audio content by searching YouTube (where most podcasts crosspost), web sources, and transcript databases. Discover relevant shows, track guest appearances, and analyze topic coverage in the podcast ecosystem.
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。
Expert SurrealDB 3 architect and developer skill (tracks v3.1.4+). SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust, Java, .NET, C, PHP, Swift, Kotlin, Ruby), Surrealism WASM extensions, SurrealML scope coverage (preview), built-in MCP (v3.1+) and standalone SurrealMCP, LangChain Python integration, editor tooling (LSP v0.1.6, tree-sitter, CodeMirror v1.0.6, VS Code/JetBrains/Neovim/Zed), and ecosystem integrations (Surrealist v3.9, Surreal-Sync, SurrealFS, SurrealKit v0.7, n8n, Agent Skills, setup-surreal). Universal skill for 30+ AI agents.
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。
Dokku is a self-hosted Platform-as-a-Service built on Docker that provides Heroku-like git-push deployment on your own infrastructure. With 32,000+ GitHub stars, it supports buildpacks, Dockerfiles, custom domains, SSL via Let's Encrypt, and a rich plugin ecosystem for databases, caching, and storage.
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。
Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).
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。
ESLint is the standard linting tool for JavaScript and TypeScript projects. It statically analyzes your code to find problems, enforce coding conventions, and catch bugs before they reach production. ESLint 9 introduced the flat config format, replacing the legacy `.eslintrc` system with a simpler, more composable `eslint.config.js` file. With a rich plugin ecosystem covering React, TypeScript, accessibility, and import ordering, ESLint is the backbone of code quality in modern web development.
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。
Manage knowledge bases and documentation with Confluence Cloud. Use when a user asks to create or manage Confluence spaces, pages, and blogs, build documentation systems, automate page creation from templates, use Confluence REST API v2, manage page trees and hierarchies, set up permissions, integrate Confluence with Jira or other tools, generate reports from Confluence data, build macros or Forge apps, or migrate content between spaces. Covers content management, API automation, templates, and Atlassian ecosystem integration.
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。
Manage repositories, pipelines, and code review with Bitbucket Cloud. Use when a user asks to set up Bitbucket repositories, configure Bitbucket Pipelines for CI/CD, manage pull requests, set up branch permissions, use Bitbucket REST API 2.0, create webhooks, manage deployment environments, set up code review workflows, integrate with Jira, configure merge checks, or automate repository operations. Covers repository management, CI/CD pipelines, code review, deployments, and Atlassian ecosystem integration.
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。
Feature-rich Stable Diffusion Web UI for image generation. Supports txt2img, img2img, inpainting, outpainting, LoRA, extensions, upscaling, and batch processing. Widely used desktop interface with an extensive extension ecosystem and API access.
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。
Actix Web is a powerful, high-performance web framework for Rust. It provides async handlers, type-safe extractors, middleware, and integrates with the Rust ecosystem for building fast, reliable, and memory-safe web services.
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。