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Build or improve UI test coverage for visual regression, interactions, and accessibility. Use when the user asks for a test strategy, automated tests, testing setup, or fixes to flaky UI tests. A one-time browser inspection or visual review does not require a new test suite.

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Implement or refine UI motion, gestures, and transitions. Use when the user asks for animation, hover or press motion, drag or swipe behavior, transition timing, or reduced-motion alternatives. Mentioning a drawer, toast, or hover state alone does not request animation.

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Tests APIs for excessive data exposure where endpoints return more data than the client application needs, relying on the frontend to filter sensitive fields. The tester intercepts API responses and analyzes them for leaked PII, internal identifiers, debug information, or sensitive business data that the UI does not display but the API transmits. This maps to OWASP API3:2023 Broken Object Property Level Authorization. Activates for requests involving API data leakage testing, excessive data exposure, response filtering bypass, or API over-fetching.

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Full review of a PR, a file, or pasted text against the OpenMetadata Writing Style Guide checklist, plus checking every checkable claim for internal consistency against the diff/PR itself. One combined report, not separate passes. Does not fetch or verify against any external source repository. Link-checking is out of scope; a separate broken-links job covers that. Only runs on explicit /content-review invocation, never self-triggered.

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Pick the right library for a given frontend task from a curated, opinionated list — numbers, OTP inputs, charts, command menus, virtualization, drag and drop, toasts, state, styling, and more. Only runs when explicitly invoked; it does not trigger on its own.

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Creates comprehensive permission tests ensuring RBAC doesn't regress with test matrices, CI gating, and authorization coverage. Use for "RBAC testing", "permission tests", "authorization testing", or "access control tests".

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Build multiple genuinely different versions of a UI piece you describe, rendered behind a visual picker so you can flip through them live and promote the one that feels right. Only runs when explicitly invoked; it does not trigger on its own.

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Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.

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Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"

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Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use improve-animations or review-animations instead.

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Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write code.

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Hunting skill for xss vulnerabilities. Built from 174 public bug bounty reports. Use when hunting xss on any target. For markup injection that reflects raw HTML but does NOT execute JavaScript (no `<script>`/event-handler execution), see hunt-html-injection — escalate here once script execution is possible.

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Perform a comprehensive read-only security audit of Clawdbot's own configuration. This is a knowledge-based skill that teaches Clawdbot to identify hardening opportunities across the system. Use when user asks to "run security check", "audit clawdbot", "check security hardening", or "what vulnerabilities does my Clawdbot have". This skill uses Clawdbot's internal capabilities and file system access to inspect configuration, detect misconfigurations, and recommend remediations. It is designed to be extensible - new checks can be added by updating this skill's knowledge.

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Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

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A brief description of what this skill does

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Analyze any codebase's source code in depth and produce structured analysis documents saved as markdown files. Use this skill whenever the user asks to understand how a codebase works — architecture, module design, call flows, data models, design patterns, performance characteristics, or any implementation detail. Trigger on phrases like "analyze the source", "explain this code", "how does X work", "where is Y implemented", "trace the flow of", "what happens when", "read through the code", "code walkthrough", "源码分析", "代码解读", "实现原理", "架构分析", "调用链路", "模块分析", or any code-exploration request. Works with any programming language: TypeScript/JavaScript, Java, Python, Go, Rust, C/C++, and more. Even if the user's question seems simple (e.g., "这个文件是干什么的"), use this skill — a thorough, source-backed analysis document is always more valuable than a surface-level guess.

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。

A brief description of what this skill does

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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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. Turn an article, doc or release note into a short explainer clip — one person to camera, or a voiceover over illustrative footage. The user supplies the source text and the model generates the speech; audio cannot be uploaded, measured. A 30-second clip holds about eighty spoken words in eight sentences — measured, and well under a tenth of a 1,200-word post — so this skill does not summarise an article, it picks the single idea worth saying and helps choose which one. Use when a user asks to turn writing into a short spoken video, e.g. "make a 30-second explainer from this blog post", "explain this feature in a short video", "turn our changelog into a clip", "a quick video explaining what this paper found". Do not use for a scene between people (see seedance-short-drama), a brand or product ad (see seedance-ad-creative), a handheld creator clip (see ugc-ads), or when the user already has both a portrait and the finished words (see talking-head). Budget sentences as well as words — each sentence boundary costs about 0.7 seconds of silence, so a script with more sentences runs longer at the same word count.

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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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Choosing and operating an HTTP API versioning strategy that doesn't break clients — Stripe's date-based pinned versions, the Deprecation/Sunset header pair (RFC 9745 + RFC 8594), URI vs header vs media-type approaches, and the version-transformer pattern. Grounded in Stripe's published architecture and IETF RFCs. NOT for GraphQL schema evolution, gRPC/Protobuf wire compatibility, database schema migrations, or library/SDK semver.

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Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

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The barber for your coding agents' config. Weighs everything every agent on this machine loads (instruction files, memory, MCP servers, hooks, skills, commands, subagents, plugins, leftovers), prices each item in tokens from your own transcripts, and parks the dead weight with a receipt and an undo. Use this skill whenever the user mentions config bloat, a heavy or slow session start, tokens burned before the first word, too many MCP servers, hooks that are slow or fire on every prompt, skills or commands or plugins nobody invokes, cleaning up or auditing CLAUDE.md or AGENTS.md, Codex config, or asks what does my agent actually load, why is my context full before I type, which of these servers can I turn off, or what is this plugin costing me. Use it even when they only say the session feels bloated or startup got slow, and even when they mention /context, /doctor or /skill-doctor.

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。