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Found 3,465 Skills
Build NFT minting experiences with Manifold's client-sdk. Guides agents through campaign setup, custom minting websites (React/Next.js), minting bots (Node.js), and SDK integration into existing projects. Supports [`Edition`](https://docs.manifold.xyz/client-sdk/sdk/product/edition-product) and [`Blind Mint`](https://docs.manifold.xyz/client-sdk/sdk/product/blind-mint) products across Ethereum, Base, Optimism, Shape, Sepolia, and ApeChain. Use when building minting pages, mint bots, integrating Manifold NFT products, or helping users set up Manifold campaigns. NOT for deploying smart contracts, managing Manifold Studio settings, or non-minting blockchain operations.
Skill for creating custom lint rules by leveraging the existing linter ecosystems of various programming languages. This is a linter designed for AI Agents rather than humans, and its error messages function as correction instruction prompts for AI. Create custom rules in the `lints/` directory using standard methods for each language, including Rust (dylint), TypeScript/JavaScript (ESLint), Python (pylint), Go (golangci-lint), etc. Use this skill in the following scenarios: (1) When you want AI to enforce project-specific coding rules; (2) When you want to create lint rules that output AI-readable correction instructions when violations occur; (3) When you want to enforce naming conventions, structural patterns, and consistency rules through AI-driven linting. Triggers: "Create a linter rule", "Add a lint rule", "Enforce this pattern", "AI linter", "Custom lint", "Code rules", "Naming rules", "Structural rules", "create a linter rule", "add a lint rule", "enforce this pattern", "AI linter".
Guides teams through designing, implementing, and optimizing CI/CD pipelines, GitHub Actions workflows, deployment automation, and agentic workflow patterns. Provides production-ready templates, cost optimization strategies, quality gates, and multi-environment deployment planning for modern DevOps practices.
Designs multi-agent system architectures with orchestration patterns, tool schemas, and performance evaluation. Use when building AI agent systems, designing agent workflows, creating tool schemas, or evaluating agent performance.
This skill should be used when inspecting, analyzing, or querying Claude Code session logs. Use when users ask about session history, want to find sessions, analyze context usage, extract tool call patterns, debug agent execution, or understand what happened in previous sessions. Essential for understanding Claude Code's ~/.claude/projects/ structure, JSONL session format, and the erk extraction pipeline.
Update all system packages and tools in parallel — winget (Windows), Windows Update (Windows), npm globals, agent skills, and apt (Linux). Each update category runs as an independent parallel task, with winget packages also upgraded in parallel internally. Use when you want to bring everything up to date quickly.
Execute AdCP Creative Protocol operations with creative agents - build creatives from briefs or existing assets, preview renderings, and discover format specifications. Use when users want to generate or transform ad creatives, preview how ads will look, or understand creative format requirements.
Context Store - Document management system for storing, querying, and retrieving documents across Claude Code sessions. Use this to maintain knowledge bases, share documents between agents. Whenever you encounter a <document id=*> in a session, use this skill to retrieve its content.
Configure and use the hosted YouTube Data MCP end-to-end with minimal user input. Use when users want the agent to verify Node.js and `npx`, configure MCP server config (Windows/macOS, Cursor/Codex/OpenClaw/OpenCode), request API key at setup time, run post-install capability discovery (`tools/list` and `get_patch_notes`), and then strongly recommend helper skill and Python setup for full local document and spreadsheet workflows.
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses the langsmith CLI tool.
Set up and manage a Tapcart CLI project. Use when the user wants to get started with Tapcart development for the first time, or manage an existing project — including auth, dependencies, linting, logs, and layout dev server. The user only needs to provide their App ID for first-time setup — the agent handles everything else.
Refines a v1 project plan into agent-ready tasks with clear context, implementation steps, and validation criteria. Use after /plan-project has produced a v1 plan.