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Found 907 Skills
Show available Kata skills, displaying the usage guide, explaining skill reference, or when the user asks for help with Kata. Triggers include "help", "show skills", "list skills", "what skills", "kata skills", and "usage guide".
Generate plain ASCII box-flow diagrams (boxes + arrows) for environments without renderers, with alignment rules and split strategies for complex graphs.
FlexLayout for React - Advanced docking layout manager with drag-and-drop, tabs, splitters, and complex window management
Analyze git changes and generate conventional commit messages. Supports batch commits for multiple unrelated changes. Use when: (1) Creating git commits, (2) Reviewing staged changes, (3) Splitting large changesets into logical commits.
Multi-instance (Multi-Agent) orchestration workflow for deep research: Split a research goal into parallel sub-goals, run child processes in the default `workspace-write` sandbox using Codex CLI (`codex exec`); prioritize installed skills for networking and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + key conclusions/recommendations summary". Applicable to: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-Agent parallel research/multi-process research".
Guide for orchestrating Claude Code agent teams — multiple parallel Claude Code sessions coordinated by a team lead. Use this skill when the user mentions agent teams, teammates, parallel agents, multi-agent workflows, spawning agents, coordinating agents, delegate mode, plan approval for teammates, TeammateIdle or TaskCompleted hooks, or wants to break a task into parallel independent work streams. Also trigger on questions about tmux split-pane mode, in-process teammate mode, Shift+Up/Down agent switching, shared task lists, inter-agent messaging, or designing tasks for multi-agent decomposition. This is an experimental feature requiring CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS to be enabled.
Develop @ant-design/agentic-ui components for AI chat interfaces. Use when creating thought chain visualization, tool call displays, markdown editors, bubble components, workspace panels, or any agentic UI development. Triggers on keywords like bubble, thought chain, tool use, markdown editor, workspace, chat layout, agentic.
Integrates and extends the ICPay crypto payments platform. Use when working with icpay-widget, icpay-sdk, payment links, merchant accounts, relay payments (recipient EVM/IC/Solana), X402 v2, refunds, split payments, email notifications, webhooks, demo.icpay.org, betterstripe.com sandbox (testnets), filter tokens/chains, WalletConnect QR and deep links, wallet adapters, currency for payment links and profile, WordPress plugins (Instant Crypto Payments, WooCommerce), registration on icpay.org, creating an account, API keys (publishable and secret), .env for keys, SDK events (icpay-sdk-transaction-completed for success, transaction lifecycle, method start/success/error), or any ICPay-related code in the icpay monorepo.
Professional data visualization creation using D3.js with support for interactive charts, custom visualizations, animations, and responsive design. Use for: (1) Creating custom interactive charts, (2) Building dashboards, (3) Network/graph visualizations, (4) Geographic data mapping, (5) Time series analysis, (6) Real-time data visualization, (7) Complex multi-dimensional data displays
Build, validate, and deploy LLM-as-Judge evaluators for automated quality assessment of LLM pipeline outputs. Use this skill whenever the user wants to: create an automated evaluator for subjective or nuanced failure modes, write a judge prompt for Pass/Fail assessment, split labeled data for judge development, measure judge alignment (TPR/TNR), estimate true success rates with bias correction, or set up CI evaluation pipelines. Also trigger when the user mentions "judge prompt", "automated eval", "LLM evaluator", "grading prompt", "alignment metrics", "true positive rate", or wants to move from manual trace review to automated evaluation. This skill covers the full lifecycle: prompt design → data splitting → iterative refinement → success rate estimation.
Design, refactor, and review Effector state management using modern v23+ patterns. Use when tasks involve createStore/createEvent/createEffect modeling, dataflow with sample/attach/split, scope-safe SSR with fork/allSettled/serialize/hydrate, React integration with useUnit, Solid/Vue integration patterns, fixing scope loss, or replacing anti-patterns such as business logic in watch, imperative calls in effects, and direct getState business reads.
Participate in QR Coin auctions on Base - bid to display URLs on QR codes