Discover AI Agent Skills

Deploy CCA (Continuous Clearing Auction) smart contracts using the Factory pattern. Use when user says "deploy auction", "deploy cca", "factory deployment", or wants to deploy a configured auction.

Search domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check domain prices, find domain deals, compare registrars, or search for .ai/.com domains.

Set up, inspect, run, build, or test the archived OpenCut Classic repository and its Bun, Next.js web, Docker services, and optional Rust/WASM paths. Use when the user explicitly mentions OpenCut Classic, opencut-classic, the legacy OpenCut web editor, or evaluating its import, timeline, preview, or export implementation. Do not use for the current OpenCut rewrite.

判断市场处于进攻、防守、震荡或切换阶段，并解释风格、广度、情绪与宏观环境的匹配关系。适用于总仓位决策、风格选择与阶段策略更新。

Explain the Ralph Loop plugin, how it works, and available skills. Use when the user asks for help with ralph loop, wants to understand the technique, or needs usage examples.

Skill for writing and updating scalar.config.json — Scalar Docs configuration reference for users and LLMs.

Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.

UV unwrap, atlas-map, project textures, use alpha decals, bake maps/lightmaps, and prepare texture-driven Blender assets for glTF/GLB export. Use whenever the user provides texture packs, texture atlases, decals, UV layouts, lightmaps, wants a texture to fit a mesh 1:1, or reports stretched/off textures. Pairs with reference-to-3d for template-accurate reconstruction and blender-materials for PBR values.

Where CometChat chat lives in a Flutter app and how to wire each shape — a tab-based app, a chat tab inside an existing app, a full-screen route, a modal / bottom-sheet chat, or an embedded panel. Triggers: 'add a chat tab', 'full screen chat page flutter', 'chat bottom sheet', 'embed chat in my screen', 'build a full chat app in flutter'.

Use when writing effective BDD scenarios including acceptance criteria, edge cases, and scenario organization. Use when defining behavior specifications.

UI/UX design intelligence for web and mobile. Includes 50+ styles, 161 color palettes, 57 font pairings, 161 product types, 99 UX guidelines, and 25 chart types across 10 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, and HTML/CSS). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, and check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, and mobile app. Elements: button, modal, navbar, sidebar, card, table, form, and chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, and flat design. Topics: color systems, accessibility, animation, layout, typography, font pairing, spacing, interaction states, shadow, and gradient. Integrations: shadcn/ui MCP for component search and examples.

Choose and write the right test type (Playwright > integration > unit) against isolated Neon branches. Use when adding, running, or debugging tests for a feature.

Migrate ESLint or other linters to Rslint. Use when asked to replace ESLint flat config, lint scripts, VS Code ESLint settings, inline directives, rules, presets, plugins, or lint dependencies with Rslint equivalents.

Feature engineering for marketplace recommenders — what to extract from raw marketplace assets (listing photos, owner-entered listing metadata, sitter wizard responses) to power item-to-item (similar listings), user-to-item (homefeed ranking), or user-to-user (mutual-fit matching) recommenders. Covers asset auditing, first-principles feature decomposition, vision-feature extraction (CLIP, room-type, amenities, aesthetics), listing text and metadata encoding, sitter wizard design, derived-composition patterns for i2i / u2i / u2u (ANN shelves, two-tower, mutual-fit), feature quality governance (training-serving parity, drift, PII), and incremental value proof (ablation A/B, kill reviews, feature-free baseline). Trigger even when the user does not explicitly say "feature engineering" but is asking how to get more signal out of listing photos, listing metadata, or the sitter onboarding wizard, or how to improve i2i / u2i / u2u quality without blindly ingesting a new model.

Use when building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for CLI design, argument parsing, interactive prompts, progress indicators, shell completions.

MUST be used whenever fixing security issues in a Flows app, or before shipping any feature that handles credentials, user input, or external data. This skill finds AND fixes security problems — it does not just report them. Do NOT skip this when the user asks for a security fix, security hardening, or vulnerability remediation — run every step in order. Triggers: security, security fix, security hardening, vulnerability, XSS, injection, credentials, secrets, auth, authentication, authorization, token, sensitive data, input validation, CORS, CSP, dependency audit.

Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps assuming engineer has minimal domain knowledge

Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (as_type, score_current_span, should_export_span, LangfuseMedia), and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.