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Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

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Extract clean markdown from any URL, including JavaScript-rendered SPAs. Use this skill whenever the user provides a URL and wants its content, says "scrape", "grab", "fetch", "pull", "get the page", "extract from this URL", or "read this webpage". Handles JS-rendered pages, multiple concurrent URLs, and returns LLM-optimized markdown. Use this instead of WebFetch for any webpage content extraction.

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Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.

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Control and interact with a live browser session on any scraped page — click buttons, fill forms, navigate flows, and extract data using natural language prompts or code. Use when the user needs to interact with a webpage beyond simple scraping: logging into a site, submitting forms, clicking through pagination, handling infinite scroll, navigating multi-step checkout or wizard flows, or when a regular scrape failed because content is behind JavaScript interaction. Also useful for authenticated scraping via profiles. Triggers on "interact", "click", "fill out the form", "log in to", "sign in", "submit", "paginated", "next page", "infinite scroll", "interact with the page", "navigate to", "open a session", or "scrape failed".

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Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.

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Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

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Analyze Claude Code features and capabilities to uncover advanced usage patterns, best practices, and real-world application scenarios. Use this skill whenever the user mentions a Claude Code feature (like Streaming Tool Execution, Hooks, MCP, Skills, Subagents, Context Management, Permission Modes, etc.) and wants to know how to leverage it effectively — including advanced tips, workflow optimizations, creative use cases, and pitfalls to avoid. Also trigger when the user pastes a feature description or asks 'how to use X better in Claude Code', even without explicitly saying 'analyze'.

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Comprehensive quality verification: spec compliance, lint, type-check, tests, cross-layer data flow, code reuse, and consistency checks. Use when code is written and needs quality verification, before committing changes, or to catch context drift during long sessions.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Turn a novel/script excerpt into an anime-style storyboard shot using the Ofox image and video APIs. Runs a short creative brief first (how many shots, the aspect ratio before any image exists, which animation look; "Let the AI decide" is offered on the taste questions, never on a must-ask one, and never as the default), generates the character with ofox-image-core — one opening frame for a single shot, a design sheet to confirm plus one opening frame per shot for a sequence — then feeds each frame to ofox-video-core as `--frame-first-image`, so every shot starts on an image of that character rather than on a text description alone. Use when a user asks to turn a story excerpt into an anime video, e.g. "turn this novel excerpt into an anime video", "make an anime-style storyboard clip of this scene", "generate a manga-drama shot with this character", or "turn this chapter into an anime short with the same character in every shot". Do not use for realistic-human dialogue scenes with no anime styling (see seedance-short-drama), silent product/brand shots (see seedance-ad-creative), or plain catalog footage (see seedance-product-video).

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Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus two real screenshots of one interface in two states. Animates the transition between them as one video — both go into a single Ofox video job, and the model cross-fades the values that changed while the rest of the layout holds. Use when a user wants a short software demo animation out of captures they already have, e.g. "turn these two screenshots into a demo clip", "show the dashboard going from the free plan to the paid one", "animate this settings change for the docs", or "make a clip of the counter going from 3 to 25". Do not use for a pair that is not a user interface (see keyframe-animation), for a screen recording (record it instead), or when only one screenshot exists.

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Handle images with ImageMagick (magick) — read metadata, resize, crop, rotate, convert format, combine images (side-by-side or grids with montage), overlay logos/watermarks, and losslessly compress with oxipng before sending. Use when the user sends an image to process, when you produce an image to deliver, or before attaching any image to a message or upload — compressing first keeps transfers fast and tokens low. Core discipline - always compress before delivering, never expose local file paths to the user, and fail open (if a tool is missing or a step errors, pass the original through unchanged; never block the task).

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Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus a publicly reachable reference video the user is authorized to use. Use when a user has a rough 3D white-model, clay, wireframe, blockout, previs, or animatic clip and wants a finished visual treatment that preserves its shot order, cut timing, camera framing, spatial layout, and motion directions. Distinguishes that structure-preserving job from a continuation beginning at the reference's final state. Do not use for two still endpoints (keyframe-animation), for appending and locally joining a new ending (video-extend-edit), or when still-image references must be combined with the video in one request — first/last-frame anchors conflict with video references in the shipped core, while mixed image/video references are untested.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Produce a set of product images to choose between — several styles, backgrounds or treatments of one product, for a listing, a store page or an ad — and quote the whole set's cost before any of it is spent. From a real product photo it edits that photo once per style, so the item stays identical across the set; for a fictional or prototype product with no photo it generates from text instead, and says what that costs in accuracy. Delegates to ofox-image-core. Use when a user asks for several product images at once, e.g. "give me 4 main images in different styles for this product", "a few background options for this photo", "some listing images for my shop", or "show this product on white, on wood, and in a lifestyle scene". Do not use for a single change to a single image (see image-edit), for video from a product photo (see seedance-product-video), or for one plain text-to-image render (that is ofox-image-core's `generate`).

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Change one thing in an image you already have and leave the rest of the picture alone — swap the background, recolour a part, remove or add an object, clean up a photo — from a local jpeg/png/webp file. Delegates to ofox-image-core's `edit` subcommand (POST /v1/images/edits, one synchronous request), prices the job with --dry-run before spending, and reports the real token cost including the uploaded picture, which is billed. Use when a user hands over an image and asks for a change to it, e.g. "change the background of this photo to a beach and keep the person unchanged", "make this button green", "remove the car in the background", or "put this product on a plain white background". Do not use to draw a new image from a text description with no input picture (that is ofox-image-core's `generate`), to produce a set of several images to choose between (see product-image), or to turn a photo into video (see seedance-product-video or seedance-ad-creative). Editing the content of an existing video — "change the background of my clip, keep the product" — has no route here and none in the video API either (measured; the mode field an edit would use is accepted and silently ignored, so nothing errors); this skill edits a single still, and routing such a request to a video skill generates brand-new footage instead of changing theirs.

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Extract brand visual system from a website or brand assets into a structured style guide

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Monitor social platforms and forums for brand mentions, category discussions, and competitor activity

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Analyzes email sequence performance metrics. Evaluates open rates, click rates, reply rates, and conversion by step. Identifies drop-off points, benchmarks against industry averages, and recommends optimizations.

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Extract and codify brand voice from existing content for consistent messaging

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Revenue forecast from pipeline data with stage-weighted probability and sensitivity analysis

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Generate structured creative briefs for ad designers with brand-consistent direction

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Generate presentation slides as self-contained HTML files with brand-consistent styling

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Audit whether a "current product focus receipt" (Decision/Now/Why-now/Evidence/Not-now/Cut-suspend/First-visible-proof/ Acceptance-gate/Kill-revisit-trigger/Owner/Review-date) and the work order it gates state a real, testable decision and a real agent launch — not planning-placeholder prose that sounds like an assignment but can't be proven. Use when deciding whether to launch an agent chain against a milestone or a stated "focus," when a work order lacks explicit input/output/owner/proof-gate, or when an acceptance gate would only prove a cached UI state instead of daemon truth. NOT for distinguishing roadmap items from energy-driven sidequests (legible-roadmap-with-sidequests), reviewing a PRD/prototype for product-completeness gaps like cold start or pricing (product-reality-reviewer), or accepting already-finished work against a personal acceptance bar (port-daddy-user-surrogate-pm-review).

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Designs, reconciles, and reviews an end-to-end Drydock program for safely staging agent runtimes: immutable worktree provenance, disposable VM containment, typed effect brokerage, global body accounting, resurrection, subscription-capacity economics, context compaction, operator control, evidence, and promotion. Use when several Drydock contracts must compose into one architecture, implementation hypertree, diagram set, or release plan. NOT for launching Port Daddy, running an untrusted subject, replacing focused containment/resurrection/capacity audits, or treating a design packet as runtime authority.

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Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

日本語の概要は準備中です。原文の説明を表示しています。