4.4万 件 ・ 関連度順
概要と使いどころ
Make a paid API request to an x402 endpoint with automatic USDC payment. Use when you or the user want to call a paid API, make an x402 request, use a paid service, or pay for an API call. Use after finding a service with search-for-service.
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X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).
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。
Promote Doppel world builds across social platforms. Use when the agent wants to share builds on Twitter/X, Farcaster, Telegram, or Moltbook to drive observers, grow reputation, and recruit collaborators.
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Interact with the BNB Chain Model Context Protocol (MCP) server. Use to query DeFi data, get token prices, search documentation, fetch git diffs, and retrieve smart contract source code on BNB Chain.
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Maintain your agent on-chain identity (ERC-8004) on BNB Chain. Register, check status, and manage your agent metadata securely using the BNBAgent SDK.
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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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。
Replace with description of the skill and when Claude should use it.
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。
Handles comprehensive resource acquisition, categorization, and asset management. Adaptive to various sources (URLs, PDFs, local paths) and centralizes media in a lowercase 'assets' folder.
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。
Converts the learning Markdown into a standalone, split-screen interactive HTML page. Left pane for EN/CN text, right pane for deep linguistic 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。
Review all uncommitted changes in the current repo and produce a structured code review report.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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 users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
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 comprehension questions and language exercises based on the analyzed content to create a complete learning loop.
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。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages.
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。
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
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Performs paragraph-by-paragraph translation and deep linguistic analysis. Explains English syntax, grammar, and sentence structure in Chinese. References assets from the raw source directory.
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look up and explain llm api pricing across models.dev, openrouter, and official provider pages. use when the user asks for model prices, input/output token costs, cached-token costs, openrouter aliases such as :free, provider-specific pricing, official versus third-party prices, or wants to verify an api call cost log.
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Discovers and injects project-specific coding guidelines from .trellis/spec/ before implementation begins. Reads spec indexes, pre-development checklists, and shared thinking guides for the target package. Use when starting a new coding task, before writing any code, switching to a different package, or needing to refresh project conventions and standards.
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Understand and customize the local Trellis architecture inside a user project. Use when modifying .trellis plus platform hooks, settings, agents, skills, commands, prompts, or workflows generated by trellis init.
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Use when entering a repository with a .ctx/ hub, or when the user asks about project context, agent instructions, tool configuration, health, candidates, broken shims, repair, or cross-tool context.
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Use when the user wants to start tracking a local custom instruction file (like .agy/ANTIGRAVITY.md or .github/copilot-instructions.md) in SuperCtx. Requires a path argument.
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Builds a hyperpersonalization packet for each lead by chaining company-researcher, cro-auditor, and person-researcher. The packet feeds into message-generator for Tier 3 personalized outreach.
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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。