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Found 558 Skills
Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRouter. Capabilities: research, fact-checking, grounded responses, knowledge retrieval. Use for: AI agents, research assistants, fact-checkers, knowledge bases. Triggers: rag, retrieval augmented generation, grounded ai, search and answer, research agent, fact checking, knowledge retrieval, ai research, search + llm, web grounded, perplexity alternative, ai with sources, citation, research pipeline
Discover and list all URLs on a website, with optional search filtering. 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", or "list all pages". Essential when the user knows which site but not which exact page.
Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.
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.
dontbesilent Concept Deconstruction. Deconstruct vague business concepts to the atomic level using Wittgenstein + Austrian economics methodology. Triggers: /dbs-deconstruct, /deconstruct-concept, "help me deconstruct this concept", "what exactly does this term mean" Concept deconstruction using Wittgenstein + Austrian economics framework. Trigger: /dbs-deconstruct, "deconstruct this concept", "what does this really mean"
Explore and understand Nx workspaces. USE WHEN answering questions about the workspace, projects, or tasks. ALSO USE WHEN an nx command fails or you need to check available targets/configuration before running a task. EXAMPLES: 'What projects are in this workspace?', 'How is project X configured?', 'What depends on library Y?', 'What targets can I run?', 'Cannot find configuration for task', 'debug nx task failure'.
Create story examples for components. Use when writing stories, creating examples, or demonstrating component usage.
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
Remove AI generation traces from text. Suitable for editing or reviewing text to make it sound more natural and more like human writing. This is a comprehensive guide based on Wikipedia's "Signs of AI writing". It detects and fixes the following patterns: exaggerated symbolic meaning, promotional language, superficial analysis ending in -ing, vague attribution, overuse of em dashes, rule of three, AI vocabulary, negative parallelism, excessive connecting phrases.
Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.