1.6万 件 ・ 関連度順
概要と使いどころ
Run the Model Context Protocol (MCP) Atlassian server in Docker, enabling integration with Jira, Confluence, and other Atlassian products. Use when you need to query Jira issues, search Confluence, or interact with Atlassian services programmatically. Requires Docker and valid Jira API credentials.
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。
Web search and content extraction via Brave Search API. Use for searching documentation, facts, or any web content. Lightweight, no browser required.
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。
Microsoft Entra ID (Azure AD) authentication for React SPAs with MSAL.js and Cloudflare Workers JWT validation using jose library. Full-stack pattern with Authorization Code Flow + PKCE. Prevents 8 documented errors. Use when: implementing Microsoft SSO, troubleshooting AADSTS50058 loops, AADSTS700084 refresh token errors, React Router redirects, setActiveAccount re-render issues, or validating Entra ID tokens in Workers.
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。
A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
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 Agent Collaborative Art Platform - 512x512 shared canvas
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_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。
Generate professional PDFs from Markdown using Pandoc and LaTeX with AI-powered content generation. Creates whitepapers, term sheets, memos, agreements, SAFEs, NDAs, and more.
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。
Write compelling business proposals that win deals. Structured templates for service proposals, project bids, and partnership pitches with proven conversion frameworks.
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 calendar events, deadlines, action items, and follow-ups from emails. Works with any calendar provider (Google, Outlook, Apple, Notion, etc.). No external dependencies — pure agent intelligence. Use when the user forwards an email, asks to check inbox for events, or wants to extract structured scheduling data from any text.
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。
Complete observability & reliability engineering system. Use when designing monitoring, implementing structured logging, setting up distributed tracing, building alerting systems, creating SLO/SLI frameworks, running incident response, conducting post-mortems, or auditing system reliability. Covers all three pillars (logs/metrics/traces), alert design, dashboard architecture, on-call operations, chaos engineering, and cost optimization.
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。
Enterprise-grade code review agent. Reviews PRs, diffs, or code files for security vulnerabilities, performance issues, error handling gaps, architecture smells, and test coverage. Works with any language, any repo, no dependencies required.
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 onboard new clients with checklists, welcome sequences, milestone tracking, and success metrics. Reduce churn by nailing the first 90 days.
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 and qualify B2B prospects using web search. Builds structured profiles with company intel, key contacts, pain points, and engagement recommendations.
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。
Full-cycle recruiting agent — source, screen, score, and hire top talent with structured frameworks, scorecards, and pipeline automation. Zero dependencies.
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。
High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and session context caching. Use for: (1) Saving agent state, (2) Caching API results, (3) Sharing data between sub-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。
Scan AI agent skills for security vulnerabilities — detects code injection, prompt injection, credential exfiltration, supply chain attacks, and 69+ threat patterns. Use when installing new skills, auditing existing ones, reviewing untrusted code, or validating packages before 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。
Turn your AI agent into a business automation architect. Design, document, implement, and monitor automated workflows across sales, ops, finance, HR, and support — no n8n or Zapier required.
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 Cloudflare DNS records, Tunnels (cloudflared), and Zero Trust policies. Use for pointing domains, exposing local services via tunnels, and updating ingress rules.
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。
Automated security auditing for OpenClaw projects. Scans for hardcoded secrets (API keys, tokens) and container vulnerabilities (CVEs) using Trivy. Provides structured reports to help maintain a clean and secure codebase.
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。
Decomposes complex user requests into executable subtasks, identifies required capabilities, searches for existing skills at skills.sh, and creates new skills when no solution exists. This skill should be used when the user submits a complex multi-step request, wants to automate workflows, or needs help breaking down large tasks into manageable pieces.
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。
Send personalized LinkedIn direct messages to a list of existing 1st-degree connections via browser automation. Use when the user wants to message LinkedIn connections with AI-personalized outreach — e.g. nurturing leads, following up after events, reconnecting with contacts, or announcing something. Takes a data file (CSV/TSV) or plain list with connection names and companies, asks for outreach context/goal, generates a tailored message per person, and sends each one via browser automation. Handles message compose flow, character limits, and incremental status tracking.
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。
Mema's personal brain - SQLite metadata index for documents and Redis short-term context buffer. Use for organizing workspace knowledge paths and managing ephemeral session state.
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。
End-to-end MegaETH development playbook (Feb 2026). Covers wallet operations, token swaps (Kyber Network), eth_sendRawTransactionSync (EIP-7966) for instant receipts, JSON-RPC batching, real-time mini-block subscriptions, storage-aware contract patterns (Solady RedBlackTreeLib), MegaEVM gas model, WebSocket keepalive, bridging from Ethereum, and debugging with mega-evme. Use when building on MegaETH, managing wallets, sending transactions, or deploying contracts.
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。