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Live SEO data via DataForSEO MCP server. SERP analysis (Google, Bing, Yahoo, YouTube), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", or "real search data".

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SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".

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。

Use when your machine does not have JuliaLang runtime

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。

Use after first-run for ongoing modpack maintenance: update/install KB packs, author or register custom/mod KB packs, maintain localization glossary KBs for translator use, prune KB cache, health-check the environment, version-pin KB/tooling, or handle recurring BGS modding environment care.

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。

Use when you need the latest stable JuliaLang version number (e.g., to fill `VERSION=` in an install script) instead of hard-coding a value

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。

AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".

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Use when planning or building the whole Bethesda modpack incrementally — batch strategy, rollback point, naming convention, separator discipline, attribution, and declaring 风格 before adding mods. Triggers - "build a modpack", "plan the pack", "batch strategy", "rollback point", "naming convention", "declare 风格", "策展整合包", "整合包规划". NOT for deciding whether one mod belongs (evaluating-bgs-mods), installing one mod from author instructions (interpreting-mod-author-instructions), load order mechanics (writing-bgs-load-order), or record conflicts (xedit-conflict-audit).

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。

Use when a BGS modded game has CTD, crash log, FPS drop, stuttering, freeze, performance, won't start, 崩溃, 掉帧, 卡顿 symptoms and the user needs a symptom-first diagnostic ladder. NOT for proactive post-install testing; use testing-bgs-modpack.

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Install and use GrayMatter as an OpenClaw skill that provides primary durable memory, shared object-graph state, and authenticated access to the live api-docs schema via api-0. Use when the agent should persist durable memory, inspect organizational data models, and operate inside the business domain through RBAC-scoped API access.

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Map tanstack ecosystem partner metadata to installable add-on ids using tanstack ecosystem --json, tanstack create --list-add-ons --json, and tanstack create --addon-details --json. Covers exclusive categories, provider options, and router-only compatibility constraints.

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INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.

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INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.

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Reapply and repair Windows Codex Desktop after Store upgrades, including custom provider models hidden by Statsig available_models filtering, the dependent blue-purple Power slider and its Ultra toggle, Fast Mode request/UI gates, locale i18n, plugin UI gates, Chrome/browser_use gates, Goal command gates, Windows Computer Use availability gates and plugin/runtime repair, phone remote-control pairing under third-party/API-key main app usage, Desktop dynamicTools/inputSchema thread-start schema drift, local conversation visibility recovery after model_provider switches, restored-conversation missing-cwd continuation repair, ASAR integrity repair, signing/installing patched MSIX packages, SDK cleanup, Fast Mode wire verification, local plugin marketplace registration, and optional custom model_instructions_file setup (the bundled system prompt, also called 听话水).

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Find and install skills from the Orthogonal skill library. Use when you need capabilities you don't have, want to discover available skills, or need to add new tools to your agent.

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Assemble a narrated-UGC "stitch reply" ad from a config — a single spoken VO carries a verbatim testimonial while ~30 per-cut i2v clips (one creator across ~5 wardrobes in ~3 worlds, plus product B-roll) are each trimmed to their EDL window built from the VO's Whisper word boundaries and hard-concatenated via filter_complex concat (never the demuxer, which drops audio on a duration mismatch), the VO mixed over an optional sidechain-ducked instrumental bed (−20dB, 20 to 1) so the VO stays on top, karaoke-pop captions burned on every word throughout (VEED Whisper preset, re-spelled against the locked script), a landing-page scroll rendered as FFmpeg zoompan over a Playwright PNG (not i2v), and closed on the brand's real end-card PNG — never AI-rendered text. This is the FREE deterministic assembly stage (trim-to-EDL + filter_complex concat + VO and music mix + karaoke captions + landing-page zoompan + end-card append), run with the shared stitch-videos-ffmpeg montage.py helper that installs with this package; the VO, creator, start-frames, and clips come from create-vo-elevenlabs / create-image-gpt-image-fal / create-image-fal / create-video-fal. Use for the narrated-ugc-wardrobe-stitch format.

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审查、安装、配置、验证、更新和移除 AgentDock Skill 时使用；负责来源校验、安全评估、环境配置、content digest、精确 skill_ref 与当前 managed 内容验收。

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Manage Simulink Real-Time target computers from MATLAB — list available targets, check whether a target is connected, read its lifecycle status, add/remove/rename targets, set IP addresses and credentials, choose the default target, install TLS material, configure a startup application, and run target lifecycle ops (connect, reboot, RTOS update). Use whenever the user asks "which targets are available", "is my target connected", "what's the status of the target", "add a Speedgoat", "switch default target", "change the target IP", "reboot the box", "update the target", or works with `slrealtime.Targets`, `tg = slrealtime`, `addTarget`, `removeTarget`, `getTargetNames`, `getDefaultTargetName`, `setDefaultTargetName`, `connect`, `isConnected`, `status(tg)`, `setipaddr`, `setupTLSCertificate`, `setStartupApp`, `reboot`, `update`, or `slrealtime.testSetup`. Covers Speedgoat target computers and Simulink Real-Time Linux devices.

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Prove that a command-line tool actually did what it said, instead of trusting its exit code and its output. Snapshots the filesystem before and after, names the expected consequence in advance, and returns one of four verdicts with what could not be seen. Use after running a build, a migration, a scaffolder, a formatter, a codegen step, or an AI coding CLI; when a command printed success and you are about to report "done"; when you are about to write "exit code 0, so it worked"; or when a tool claims it edited files. Needs nothing installed.

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Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.

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。

Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.

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Manages iOS Simulator devices and app tests with xcrun simctl: lifecycle, install/launch, push and location simulation, privacy permissions, deep links, status-bar overrides, screenshots/video, log streaming, app containers, and targetEnvironment(simulator). Use when scripting Simulator workflows, debugging CoreSimulator boot failures, or deciding which hardware, performance, networking, memory-pressure, and security behaviors require a physical device.

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Create Viking web projects, start and verify a local preview, or deploy a generated project to Volcengine IGA Pages when explicitly requested. Includes agent-guided feature, eligible application, dataset, scene, and authentication choices. Use only after confirming the installed CLI exposes `vs project`; otherwise stop without taking action.

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Answer Viking AI Search product questions, CLI usage questions, API/auth questions, configuration questions, and troubleshooting questions by grounding every claim in either the installed `vs` CLI's own output or official Volcengine documentation. Never fabricate.

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Guide a brand-new SearchCLI/vs user from first-time usage questions to sign-up, purchase of Viking AI Search, AK/SK setup, and a working authenticated CLI. Use when the user says they downloaded or installed SearchCLI/vs and asks how to use it, how to start, sign up, buy, or onboard.

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。