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概要と使いどころ
Automated web form filling and file uploading skill with Playwright browser automation. Handles login persistence, form detection, file uploads, and waits for manual confirmation before submission.
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 hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa
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。
小红书图片策划与自动生图。将内容拆解为系列卡通风格信息图提示词，通过 Chrome DevTools MCP 自动化调用 Gemini web app 生成图片，并自动收集到本地临时目录。当用户提到"小红书"、"信息图"、"rednote"、"生图"、"图片策划"、"小红书配图"、"Gemini生图"、"nano banana"、或将内容制作成小红书图片时触发此技能。包含完整的提示词生成、浏览器自动化和图片收集全流程。
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 Claude Code features and capabilities to uncover advanced usage patterns, best practices, and real-world application scenarios. Use this skill whenever the user mentions a Claude Code feature (like Streaming Tool Execution, Hooks, MCP, Skills, Subagents, Context Management, Permission Modes, etc.) and wants to know how to leverage it effectively — including advanced tips, workflow optimizations, creative use cases, and pitfalls to avoid. Also trigger when the user pastes a feature description or asks 'how to use X better in Claude Code', even without explicitly saying 'analyze'.
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。
Free AI search via Exa MCP. Web search for news/info, code search for docs/examples from GitHub/StackOverflow, company research for business intel. No API key needed.
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。
Determines all follow-up actions due today across the 10-day outreach cadence. Generates content and delivers automatically via Chrome DevTools MCP. Sends Telegram confirmation after completion.
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。
Generates and delivers all outreach for OUTREACH_READY leads. Automated delivery via Chrome DevTools MCP -- email, LinkedIn, Instagram. Gig leads auto-applied on platform. No approval gates.
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 daily sales pipeline execution. Run at 9 AM via cron. Scans for signals, enriches company leads, auto-applies to gigs, runs multi-channel outreach, processes follow-ups. All delivery automated via Chrome DevTools MCP.
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。
Find phone numbers for decision makers via Lemlist using Chrome DevTools MCP. Takes LinkedIn profile URLs and returns phone numbers where available.
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。
Find 5 decision makers at a company via Apollo.io UI using Chrome DevTools MCP. No enrichment, no credits used.
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。
Find and validate email addresses using Snov.io via Chrome DevTools MCP. Takes LinkedIn profile URLs and returns verified emails. Replaces ZeroBounce.
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。
Check all outreach channels for replies using Chrome DevTools MCP. Scans Zoho webmail, LinkedIn messaging, and Instagram DMs.
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。
Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Deduplicates against CRM (Google Sheets). Supports Apollo API and MCP tools.
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 and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details.
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。
Prepare for Anthropic-specific technical interviews covering Constitutional AI, RLHF, interpretability, scaling laws, MCP, agentic systems, and AI safety. Activate on "anthropic interview", "constitutional AI prep", "alignment interview", "safety interview", "RLHF opinion", "interpretability prep", "anthropic technical". NOT for general ML interview prep, system design interviews, coding challenges, or behavioral interview practice.
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。
Build stateful Agents on Cloudflare Workers with current, source-verified SDK APIs. Covers durable state, RPC, chat, schedules, queues, fibers, Workflows, MCP, and channels while keeping authorization and external effects application-owned. NOT for assuming SDK helpers grant application authorization or effect approval.
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。
Design and scaffold new skills, subagents, and MCP surfaces. Use when choosing which primitive to create. NOT for invoking existing agents, generic coding help, or deployment work.
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。
OneClickVirt operations skill for managing containers, virtual machines, provider nodes, health checks, and metrics through MCP.
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。
Drive a native GUI app (macOS, Windows, Linux) via the cua-driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host.
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 security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.
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。
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
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。
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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。
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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。