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Remove Gemini AI watermarks from images using GeminiWatermarkTool (GWT). Use this skill whenever the user mentions: Gemini watermark, 浮水印, AI image cleanup, removing logos from Gemini-generated images, Google ImageFX cleanup, batch processing AI-generated photos, or anything about a semi-transparent logo in the bottom-right corner of an image — even if they don't say "GeminiWatermarkTool" explicitly. Also trigger for follow-up requests like "the corner still looks dirty" or "there's still residual artifacts" after a previous removal attempt.

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Use at a cognee hackathon. Watches the participant's experience with cognee throughout the session — errors, slowness, confusion, workarounds, and signs of frustration in how they work with you — and keeps one private feedback file they send to the cognee team at the end.

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。

Safely clean regenerable clutter from a project folder by scanning for build artifacts and caches, backing up every removed path into a timestamped archive with a BACKUP.md manifest, zipping the backup to save space, and only deleting originals after explicit confirmation. Use when the user asks to clean a project directory, remove node_modules, clear build output, reclaim disk space, or tidy a repo before archiving.

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 PROJECT_GUIDE.md exists, when the user asks if a project is worth their time, should they build vs buy, or invokes project-worth-my-time. Follow-up to explain-new-project—weighs project context (files, git history, chat) to recommend whether to invest in a repo, cherry-pick a feature, park the idea, pass, or use an existing polished product instead. Optionally enriched by a personal-memory MCP (e.g. Pieces) when one is available.

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Use when exposing app features to App Intents, Shortcuts, Siri, Spotlight, widgets, controls, or system actions — small safe AppIntents, AppShortcutsProvider, AppEnum/AppEntity, parameters, and open-vs-background behavior.

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Use when designing or implementing empty, first-run, no-result, offline, error, or waiting states in Apple-platform apps — every empty state explains what is missing, why it matters, and what to do next.

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Teach the user exactly ONE thing from the current session or project, in plain English, one or two short paragraphs. Use when the user types ;til or "til", asks "what did I learn", "explain one thing from this session", or at session close alongside other closing rituals. Also appropriate mid-session when a concept keeps recurring that the user clearly hasn't used themselves. One thing only — never a list, never a lecture.

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 returning to a repo after a break, asking what changed, what's new for this stack, or invoking project-catch-up after explain-new-project. Scans the stack for important updates, deprecations, new helper tools, agent skills, and MCP servers online—plain-language brief saved as PROJECT_CATCH_UP.md.

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Use when a macOS app needs a TCC permission or touches private data — the map of which API, Info.plist key, and entitlement each permission needs, pre-prompt explanation patterns, denied-state recovery with System Settings deep links, and honest privacy copy.

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Use when the user wants the full package on a repo, says run my project workflow, project check-in, or is overwhelmed opening an old or new folder. Runs the project onboarding checklist—explain-new-project, project-worth-my-time, and project-catch-up—in order or on demand.

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。

Unanchored expert verdict on the open decision, checked against the current state of the art.

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Apply personal Git conventions when committing, creating or updating PRs, merging, rebasing, or explicitly shipping work end to end.

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。

Explore competing approaches through independent agents before selecting an implementation.

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Re-analyze an existing GitHub Issue using its current title and body as input, refresh the implementation plan against the latest code state, and update the Issue in place. Use this when the user provides an Issue number (numeric, `#`-prefixed, or Issue URL) and wants to regenerate the Explore-based analysis. For reflecting comment-driven updates instead, use update-issue. For creating a brand-new Issue from a natural-language task description, use create-issue.

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Virtual QA Lead that turns requirements into review-ready, TestRail-importable test cases in one conversation. Use it whenever the user has requirements, a spec, a user story, or acceptance criteria (PDF, DOCX, XLSX, TXT, MD, or pasted text) and wants test cases, a test plan, a checklist, test coverage, a regression suite, or a TestRail/Qase/Zephyr export, even without saying "test cases" ("write tests for this spec", "what should we check here?"). Especially useful when they attach their team's existing test cases to match. When the spec describes an API (endpoints, status codes, schemas, auth, OpenAPI/Swagger), Casely also builds a runnable Postman collection, so use it for "API tests", "Postman collection", or "tests I can run in Newman/CI". Triggers on the same request in any language.

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Transforms data into compelling visual narratives by applying narrative structure, annotation techniques, scrollytelling patterns, and honest framing to data journalism, presentations, and infographics. Use when creating data-driven articles or reports, designing infographics with narrative, building scrollytelling experiences, annotating charts to guide interpretation, or when user mentions data storytelling, presentation design, annotated chart, narrative visualization.

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Audit or update this Windows computer's fixed third-party Codex helper toolchain when the user requests local helper-tool maintenance. Always show the complete registered list and obtain confirmation for each update group; exclude Codex itself and general runtimes unless explicitly added.

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Produce comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.

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 encountering any bug, test failure, or unexpected behavior, before proposing fixes

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Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

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。

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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把多页 HTML 报告(主页 + N 子页 + PNG 资产)合并为单一独立 HTML / PDF / XLSX 三件交付物。 Use when finalizing a disease market sizing report and need shareable deliverables — single-file HTML for email/IM(零依赖,双击浏览器开), optional PDF for print/archive, XLSX for data export. 领域无关、跨疾病通用。 下游 of disease-market-sizing-html-template;上游 of email/IM/print 分发。 Use proactively whenever the user says "做交付物" / "生成 PDF" / "导 Excel" / "合并单文件 HTML"。

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。

WeChat Mini Program development skill for building, debugging, previewing, testing, publishing, and optimizing mini program projects. This skill should be used when users ask to create, develop, modify, debug, preview, test, deploy, publish, launch, review, or optimize WeChat Mini Programs, mini program pages, components, `tabBar`, routing, navigation, icon assets, project structure, project configuration, `project.config.json`, `appid` setup, device preview, real-device validation, WeChat Developer Tools Nightly workflows, `wechatide` CLI, WeChat IDE Skills/MCP, console/network debugging, `miniprogram-ci` preview/upload flows, or mini program release processes. It should also be used when users explicitly mention CloudBase, `wx.cloud`, Tencent CloudBase, 腾讯云开发, 微信云开发, or 云开发 in a mini program project.

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 this skill when a user asks to polish, rewrite, humanize, de-AI, localize, or oralize Chinese writing, including short-video scripts, articles, social posts, speeches, newsletters, and personal-IP content. The skill diagnoses “AI味”, preserves the user's meaning, adapts to optional style samples, replaces translation-like phrasing with natural Chinese expression, and outputs a polished version plus concise revision notes.

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。