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Found 575 Skills
Deposit and bridge funds into a wallet or protocol using Swapper Finance. Handles fiat on-ramp (card payments via Mastercard, Visa, Apple Pay, Google Pay), crypto transfers, and cross-chain bridging via Chainlink CCIP — directly into lending, staking, and liquidity protocols. Supports Ethereum, Base, Arbitrum, Optimism, Polygon, Solana, BNB Chain, Avalanche, Fast, HyperEVM and more. 170+ countries supported. Powered by Chainlink CRE and Mastercard. Triggers when the user wants to deposit, fund, top-up, buy crypto, or bridge assets into a wallet. Also triggers mid-reasoning when you detect that a wallet has insufficient funds, missing tokens, or needs funding before another operation can proceed.
Use this skill when creating and configuring a PixiJS v8 Application. Covers new Application() + async app.init() options (width, height, background, antialias, resolution, autoDensity, preference, resizeTo, autoStart, sharedTicker, canvas, useBackBuffer, powerPreference, eventFeatures, accessibilityOptions, gcActive, bezierSmoothness, webgl/webgpu/canvasOptions per-renderer overrides), app.stage/renderer/canvas/screen/domContainerRoot access, ResizePlugin, TickerPlugin, CullerPlugin (cullable, cullArea), custom ApplicationPlugin creation via ExtensionType.Application, start/stop lifecycle, and app.destroy() with releaseGlobalResources. Triggers on: Application, app.init, app.stage, app.renderer, app.canvas, app.screen, app.domContainerRoot, ApplicationOptions, ApplicationPlugin, ExtensionType.Application, resizeTo, preference, autoStart, sharedTicker, useBackBuffer, powerPreference, skipExtensionImports, preferWebGLVersion, preserveDrawingBuffer, cullable, CullerPlugin, app.start, app.stop, app.destroy, releaseGlobalResources.
A world-class radiologist specializing in multimodality image interpretation (CT, MRI, X-ray, ultrasound, nuclear medicine), structured reporting (BI-RADS, TI-RADS, Fleischner Society, LI-RADS), Use when: healthcare, radiology, medical-imaging, CT, MRI.
Use when needing to leverage popular topics, trending hashtags, seasonal events, or viral content to accelerate growth and increase visibility
Maintainer workflow for reviewing, triaging, preparing, closing, or landing OpenClaw pull requests and related issues. Use when Codex needs to validate bug-fix claims, search for related issues or PRs, apply or recommend close/reason labels, prepare GitHub comments safely, check review-thread follow-up, or perform maintainer-style PR decision making before merge or closure.
Draft or update requirement documents under `codestable/requirements/` for the project — use **user stories + plain language** to describe a capability's "reason for existence, solution approach, and boundaries", so non-technical readers can quickly understand the highlights of the system. Layered with architecture: requirement is the "problem space" (why this capability is needed), while architecture is the "solution space" (what structure is used to implement it). Two modes: new (draft a new requirement doc from scratch), update (refresh an existing doc based on new materials or implementation changes). Single-target rule — only modify one document at a time. Trigger scenarios: the user says "fill in a requirement doc", "write down the requirements for this capability", "update the requirements directory", or during the feature-design phase, it is found that there is no corresponding requirement for the capability to be implemented this time.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Every Open-Meteo endpoint family in one CLI — forecast, archive, marine, air quality, flood, climate, ensemble, seasonal, geocoding, elevation. Trigger phrases: `what's the weather in`, `forecast for`, `is it going to rain`, `marine forecast`, `air quality in`, `historical weather`, `climate normal`, `use open-meteo`, `run open-meteo`.
Plan an Israeli wedding from engagement to chuppah, covering venue selection (ulmot, ganot aruim), vendor comparison via Israeli platforms (Celebrate, Engaged, Save A Date, Walla Wedding), budget planning (~100-140K NIS average), Rabbinate registration (tik nisuin, teudat ravakut), halachic requirements (mikveh, ketuba), guest management, per-plate cost optimization, seasonal pricing, and timeline creation. Use when user asks about "chatuna b'yisrael", Israeli wedding planning, wedding budget, "ulam aruim", "ulmot", "ganim", wedding vendors, Rabbinate requirements, "tik nisuin", ketuba, or wedding timeline. Prevents common mistakes like missing Rabbinate deadlines, overpaying on Thursday weddings, or forgetting AKUM fees. Do NOT use for destination weddings abroad, non-Jewish religious ceremonies, or divorce proceedings.
High-converting landing pages — campaign pages, collection pages, seasonal promos, A/B testing
Use when the user is doing AI/ML work in a scientific domain — biology, chemistry, physics, astronomy, climate, genomics, materials science, medicine, ecology, energy, conservation, engineering, mathematics, scientific reasoning, drug discovery, protein design, weather modeling, theorem proving, single-cell, PDE solving, or anything similar. Hugging Science (huggingscience.co) is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces; the `hugging-science` org on Hugging Face hosts community datasets, models, and demo Spaces. This skill helps you discover the right resource AND actually use it — loading datasets via `datasets`, running models via `transformers` or the HF Inference API, calling Spaces like BoltzGen via `gradio_client`, and citing blog posts for methodology. Trigger this skill whenever a user mentions a scientific ML task, asks for "a dataset/model for X" where X is a scientific topic, wants to fine-tune on scientific data, asks about protein / molecule / genome / climate / materials / astronomy / pathology / weather ML, or needs AI tools for research — even if they never say "Hugging Science" explicitly. The catalog is purpose-built for LLM agents (it ships an `llms-full.txt`); prefer it over generic web search for these tasks.
Reviews PR comments from GitHub (Copilot, reviewers), evaluates against actual code, replies with reasoning, and resolves threads. Triggers on "review pr comments", "address pr feedback", "fix pr comments", or "review copilot suggestions".