'local' 검색 결과

Fetch, preview, merge, and test GitHub PRs locally. Great for trying upstream PRs before they're merged.

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Use the Fly.io flyctl CLI for deploying and operating apps on Fly.io: deploys (local or remote builder), viewing status/logs, SSH/console, secrets/config, scaling, machines, volumes, and Fly Postgres (create/attach/manage databases). Use when asked to deploy to Fly.io, debug fly deploy/build/runtime failures, set up GitHub Actions deploys/previews, or safely manage Fly apps and Postgres.

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Smart ClawdBot documentation access with local search index, cached snippets, and on-demand fetch. Token-efficient and freshness-aware.

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Climb the browser ladder — start free, escalate only when needed. L1 (fetch) → L2 (local Playwright) → L3 (BrowserCat) → L4 (Browserless.io for CAPTCHA/bot bypass).

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This skill enables IP address masking and accessing hidden services on the Anyone Network. Route requests through the Anyone Protocol VPN network using a local SOCKS5 proxy.

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Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

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Manages a local CSV-based CRM with pipeline tracking

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Manage and monitor local Pi-hole instance. Query FTL database for statistics (blocked ads, top clients) and control service via CLI. Use when user asks "how many ads blocked", "pihole status", or "update gravity".

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Manage Cloudflare DNS records, Tunnels (cloudflared), and Zero Trust policies. Use for pointing domains, exposing local services via tunnels, and updating ingress rules.

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Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

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Handles comprehensive resource acquisition, categorization, and asset management. Adaptive to various sources (URLs, PDFs, local paths) and centralizes media in a lowercase 'assets' folder.

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Web scraping, search, crawling, and page interaction via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, extract data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference scraping external websites. This provides real-time web search with full page content extraction and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

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Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

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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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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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Securely store, search, and use secrets (API keys, tokens, passwords, SSH keys) with hal-vault, an SSH-key encrypted local secret store. Use when the user shares a credential that should be saved, asks what secrets are stored or where a key is, or when a command/workflow needs a secret injected. Core discipline - never print raw secret values into chat, logs, or files; reference secrets only by their masked form, and use --reveal only to feed another process, never into a command argument (where it lands in the machine's process table) or into text you write down.

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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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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. Shared execution layer for the Ofox image API (api.ofox.ai) — validates parameters client-side, sends one synchronous request, base64-decodes the result, saves it to a file, and reports the real usage token counts and the computed dollar cost. Does both text-to-image (generate) and editing an existing image you supply as a local file (edit — change the background, recolour an element, alter a product photo, while leaving the rest of the picture intact). This is a library skill, not a standalone user-facing one — it is meant to be invoked by scenario skills that build model/prompt/size choices for a specific use case and then call into this skill's script rather than re-implementing the API calls — image-edit owns "change this image so that...", product-image owns a set of product images to choose between, and seedance-anime-drama owns character images for a video pipeline. Load this skill directly only when a user explicitly names the Ofox image API, asks to call it with specific low-level parameters, asks to debug a failed Ofox image request, or wants a plain "generate an image of..." from text — which is the one common case no scenario skill covers.

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Understand and customize the local Trellis architecture inside a user project. Use when modifying .trellis plus platform hooks, settings, agents, skills, commands, prompts, or workflows generated by trellis init.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus the music file the finished video must carry. Your audio never reaches the API (measured) — the visuals are written to the track's tempo, mood and sections, then your own file is laid on locally at zero cost. One job caps at 30 seconds, so a three-minute song is six jobs minimum and the cost table says that before anything is spent. Use when a user has a specific piece of music and wants visuals for it, e.g. "make a music video for this track", "visuals for my song", "an MV for this instrumental", "generate footage cut to this beat". Do not use for cheap vertical social drafts (shorts-reels), a brand film that happens to have a music bed (seedance-ad-creative), or when there is no particular audio file the finished video has to carry.

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Use when the user wants to start tracking a local custom instruction file (like .agy/ANTIGRAVITY.md or .github/copilot-instructions.md) in SuperCtx. Requires a path argument.

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Use when you need to visually interact with a GUI — test buttons, fill forms, verify visual layouts, fuzz web pages, automate user flows, take screenshots, or perform end-to-end QA on any application. Works on cloud VMs, Docker containers, local machines, and sandboxes. Install: pip install cua.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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