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概要と使いどころ

math-slop

無料

Generate satirical "math slop" ragebait formulas that connect famous constants (φ, π, e, i) in trivially true but profound-looking equations. Outputs LaTeX. Use for math memes or when someone asks for "math slop."

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

Complete Open WebUI API integration for managing LLM models, chat completions, Ollama proxy operations, file uploads, knowledge bases (RAG), image generation, audio processing, and pipelines. Use this skill when interacting with Open WebUI instances via REST API - listing models, chatting with LLMs, uploading files for RAG, managing knowledge collections, or executing Ollama commands through the Open WebUI proxy. Requires OPENWEBUI_URL and OPENWEBUI_TOKEN environment variables or explicit parameters.

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

Build and deploy a paid API that other agents can pay to use via x402. Use when you or the user want to monetize an API, make money, earn money, offer a service, sell a service to other agents, charge for endpoints, create a paid endpoint, or set up a paid service. Covers "make money by offering an endpoint", "sell a service", "monetize your data", "create a paid API".

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

AI-powered Reddit seeding agent for founders. Analyzes a product spec, maps relevant subreddits, finds real threads where target users need help, drafts personalized replies and DMs, and posts approved outreach via Reddit API. Use when someone wants to find and engage their first users on Reddit, seed a product launch, or do community-led growth without a budget.

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。

johnalbertini14-glitch/openclaw-skills22026年2月26日 更新

firecrawl

無料

Web scraping, search, crawling, and page interaction via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, extract data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference scraping external websites. This provides real-time web search with full page content extraction and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing 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。

Scoheart/agentskills22026年8月4日 更新

Extract clean markdown or text content from specific URLs via the Tavily CLI. Use this skill when the user has one or more URLs and wants their content, says "extract", "grab the content from", "pull the text from", "get the page at", "read this webpage", or needs clean text from web pages. Handles JavaScript-rendered pages, returns LLM-optimized markdown, and supports query-focused chunking for targeted extraction. Can process up to 20 URLs in a single call.

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。

Scoheart/agentskills22026年8月4日 更新

Control and interact with a live browser session on any scraped page — click buttons, fill forms, navigate flows, and extract data using natural language prompts or code. Use when the user needs to interact with a webpage beyond simple scraping: logging into a site, submitting forms, clicking through pagination, handling infinite scroll, navigating multi-step checkout or wizard flows, or when a regular scrape failed because content is behind JavaScript interaction. Also useful for authenticated scraping via profiles. Triggers on "interact", "click", "fill out the form", "log in to", "sign in", "submit", "paginated", "next page", "infinite scroll", "interact with the page", "navigate to", "open a session", or "scrape failed".

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。

Scoheart/agentskills22026年8月4日 更新

Discover and list all URLs on a website without extracting content, via the Tavily CLI. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", "list all pages", or "site structure". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.

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。

Scoheart/agentskills22026年8月4日 更新

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。

Scoheart/agentskills22026年8月4日 更新

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.

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。

Scoheart/agentskills22026年8月4日 更新

Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.

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。

Scoheart/agentskills22026年8月4日 更新

Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.

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。

Scoheart/agentskills22026年8月4日 更新

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

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。

Scoheart/agentskills22026年8月4日 更新

Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing 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。

Scoheart/agentskills22026年8月4日 更新

Resume work on the current task. Loads the workflow Phase Index, figures out which phase/step to pick up at, then pulls the step-level detail via get_context.py --mode phase. Use when coming back to an in-progress task and you need to know what to do next.

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。

ofoxai/skills22026年9月22日 更新

Enriches inbound leads with firmographic and technographic data. Takes minimal lead info and enriches via WebSearch, Apollo, or ZoomInfo to produce a complete lead record with company size, revenue, tech stack, social profiles, and decision-maker 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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

Read and write data to the agency CRM (Google Sheets via webhook or API)

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

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。

ekatasingh1107/b2b-gtm-skills22026年4月12日 更新

Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs. NOT for OTel metrics/logs pipelines, vendor backend setup (Datadog/Honeycomb/Jaeger/Tempo), or browser RUM tracing.

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。

curiositech/port-daddy22026年10月12日 更新

Design and implement systematic checklists that reduce errors by 30-50% in complex, high-stakes domains (medicine, aviation, construction, finance). NOT for simple tasks or when comprehensive instruction is 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。

curiositech/port-daddy22026年10月12日 更新