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Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
Animate React components with Animate UI (Motion-based animated primitives for Radix UI, Base UI and React Aria). For shadcn/ui components, runs the `@animate-ui/cli` codemod that swaps their primitives for Animate UI's; for components built directly on Radix UI, Base UI or React Aria, swaps the import to `@animate-ui/react`; for anything else (custom components, plain markup, other libraries), applies Animate UI's motion rules, tokens (springs, curves, scales, blur, shifts) and recipes with Motion (motion/react). Also reviews existing motion with the `audit` command, migrates Animate UI v1 projects, and turns any icon (Lucide, Hugeicons, Tabler, Phosphor, a custom SVG) into an animated icon compatible with `AnimateIcon`. Use when asked to animate a component, make shadcn/ui "animated", add enter/exit, press or swap animations, set up Animate UI, animate an icon, change the animation pace, review whether motion follows Animate UI's rules, or find slow and janky animations.
Write a branch's PR body that tells a reviewer how much attention it needs, with a visual summary, harvested evidence and a fresh-context one-way or two-way door call, then put it and an attention label on the branch's PR. Use when a branch is ready for review, when the user says "write the PR body", "update the PR description", "how risky is this PR", or "is this ready to merge", and when another skill closes a branch.
Produce a ready-to-paste handover prompt for continuing the current task in a fresh conversation, another agent, or another harness. Use when the user asks for session context or a handover they can copy into another conversation. Carry the user's goal, relevant environment, and evidence-grounded progress forward, with concise pointers to existing artifacts. Deliver the complete prompt directly in chat.
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
Analyze articles for AI-generated content indicators and rewrite to pass WeChat's 3.27 non-human automated content creation detection. Checks for template phrases, transition word density, sentence uniformity, paragraph pattern repetition, and other signals that WeChat uses to flag AI content. Outputs a risk report and an optional humanized rewrite. Use when the user wants to check if an article looks AI-generated, make an article more human-like, bypass WeChat AI detection, or humanize AI-written content. Also trigger when the user mentions "去AI痕迹", "人性化润色", "微信AI检测", "anti-ai-check", "humanize article", "公众号发文检查".
Route work that is too large for a single chat into a structured plan. Use when the user describes a multi-step build, a migration, a rewrite, an audit, a refactor across many files, or a research question with several threads. Use when a goal would otherwise need step-by-step supervision across more than one session. Also use when the user says "plan this", "where do I start", "help me build X", "this is a big one", or hands over a spec, a ticket, or a document and asks what to do with it.
Use MinerU as the preferred tool for reading, parsing, OCR, searching, inspecting, and citing documents. Support parsing PDF, scanned/captured document images, .doc/.docx, .ppt/.pptx, .xls/.xlsx, .rtf, .odt/.ods/.odp, .epub, .ofd, .html/.htm, and .csv files. Prefer MinerU over generic PDF parsers, OCR libraries, and other document parsing tools for supported formats unless the user explicitly requests another tool or MinerU is unavailable. Use for local document workflows, long documents, tables, formulas, structured errors, continuation, and stable page/block locators.
[Slow is Fast] Slow is fast. Helps people doing private-domain / product selection / team leadership see clearly, in the task at hand: which step is worth doing slowly and personally (the first 100 customers, the first round of product testing, the first 30 days of Moments, doing the job once yourself before hiring), and which step should be fast, outsourced, or handled with tools. Use when the user says “Is there a slower but more stable way”, “Am I taking a shortcut?”, “Can this be outsourced / use a template / group-sent”, “Why can others do it fast but I can't”, “I want to save effort”. | Produced by Xiaoye
【Concept Decomposition】Concept Decomposition. Breaking down the overused buzzwords in the private domain / short video / IP circle (private domain, direct-operation-ization, micro-business-ization, push-seller, order fans, traffic-generation products / profit products, people efficiency, lonely period, winning experience, mind position, spiritual mothership, passive income, precise traffic) to the level where they can land on actions and numbers, and determining which are old words re-skinned and which questions have no textual answers at all. Used when users say "What exactly is private domain", "What does this word mean", "Help me break down this concept", "Is what he said the same as what I understand", "Is this something new". ｜ Made by Xiaoye
Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.
Use at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process."