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Found 4,154 Skills
Configure and build Model Context Protocol (MCP) servers for Claude Code integration. Set up database, filesystem, git, and API connections. Build custom MCP servers with TypeScript/Python SDK, implement tools and resources, configure transports (stdio, HTTP), and deploy for production.
Monorepo tooling, task orchestration, and workspace architecture for JavaScript/TypeScript repositories. Use when setting up Turborepo, Nx, pnpm workspaces, or npm workspaces; designing package boundaries; configuring remote caching; optimizing CI for affected packages; managing versioning with Changesets; or untangling circular dependencies. Activate on "monorepo", "turborepo", "nx", "pnpm workspace", "task pipeline", "remote cache", "changesets", "CODEOWNERS", "circular dependency", "affected packages", "workspace". NOT for git submodules or multi-repo federation strategies, non-JavaScript monorepos (Bazel, Pants, Buck), or single-package repository setup.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
Use this skill to manage already-installed skills across Claude Code, Codex, Gemini, OpenCode, OpenClaw, Cursor, Copilot, and other configured agent tools by comparing skill status and linking from configured source directories such as ~/.cc-switch/skills/ and ~/.agents/skills/. Trigger it in two major cases: first, when the user wants to sync, remove, repair, or align skills or agent skills across multiple agents; second, when the user does not yet know the current skill state and wants to inspect skill differences, missing skills, per-agent skill coverage, per-skill coverage, or decide what skill changes to make next. Use this skill when the topic is cross-agent skill or agent-skill management, not for general agent comparison, general model capability questions, or creating, editing, or installing skills from GitHub.
Full-cycle revenue engine — prospecting, CRM pipeline management, closing deals, partnerships, and engineering-as-marketing. External sales via GitHub and web.
AI-powered adversarial UI testing via the browse CLI. Analyzes git diffs to test only what changed, or explores the full app to find bugs. Tests functional correctness, accessibility, responsive layout, and UX heuristics. Use when the user asks to test UI changes, QA a pull request, audit accessibility, or run exploratory testing. Supports local browser (localhost) and remote Browserbase (deployed sites).
Define an entire Cargo workspace in code — connectors, models, plays, tools, agents, MCP servers, context, capacities, territories, segments, folders, files, workers, apps — and deploy it declaratively with `cargo-ai cdk` (init → types → plan → deploy), the way you'd manage cloud infra with Pulumi or the AWS CDK. Use when the user wants to manage Cargo resources as code: reproducibly, version-controlled, in git, from a template, or across environments. Routes to authoring/deploy/typing guides (Level 2), recipes (Level 2.5), and references. For one-off imperative operations (create one connector, read a model, run a workflow), use the matching capability skill instead.
Semantic code search using mgrep for efficient codebase exploration. This skill should be used when searching or exploring codebases with more than 30 non-gitignored files and/or nested directory structures. It provides natural language semantic search that complements traditional grep/ripgrep for finding features, understanding intent, and exploring unfamiliar code.
MUI Base UI style guidelines for building headless React component libraries (formerly headless-ui-style). This skill should be used when creating unstyled UI components, compound components with render props, accessibility-first patterns, or component libraries that separate logic from styling. Extracted from the MUI Base UI codebase (github.com/mui/base-ui).
The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.
HTTP actions for webhooks and API endpoints in Convex. Use when building webhook handlers (Stripe, Clerk, GitHub), creating REST API endpoints, handling file uploads/downloads, or implementing CORS for browser requests.
Generate a production-ready AbsolutelySkilled skill from any source: GitHub repos, documentation URLs, or domain topics (marketing, sales, TypeScript, etc.). Triggers on /skill-forge, "create a skill for X", "generate a skill from these docs", "make a skill for this repo", "build a skill about marketing", or "add X to the registry". For URLs: performs deep doc research (README, llms.txt, API references). For domains: runs a brainstorming discovery session with the user to define scope and content. Outputs a complete skill/ folder with SKILL.md, evals.json, and optionally sources.yaml, ready to PR into the AbsolutelySkilled registry.