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Found 546 Skills
Model Selection and Recommendation for Alibaba Cloud Tongyi Wanli. Activated when users need to "select, recommend, compare" models, or describe an AI scenario/functional requirement (implying the need to decide which model to use). The core intention is to help users make decisions, not just provide information. Trigger words: recommend model, which one to choose, which is suitable, compare, build a XX, implement XX function, which model is good to use, XX scenario solution. When users involve both model query and model selection at the same time, prioritize using this skill (this skill will read model data internally to complete the recommendation).
Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products.
Straightforward text extraction from document files (text-based PDF only for now, no OCR or docx). Use when you just need to read/extract text from binary documents.
Query, audit, and optimize Google Ads campaigns. Supports two modes: (1) API mode for bulk operations with google-ads Python SDK, (2) Browser automation mode for users without API access - just attach a browser tab to ads.google.com. Use when asked to check ad performance, pause campaigns/keywords, find wasted spend, audit conversion tracking, or optimize Google Ads accounts.
This skill should be used when the user: - Wants to work on multiple branches simultaneously or in parallel - Needs to start a new feature/task while preserving current work - Asks about git worktree operations (create, remove, list, clean) - Mentions "twig" commands (add, remove, clean, list, init) - Wants to carry or move uncommitted changes to a new branch - Wants to copy/sync changes between branches - Needs to isolate work in a separate directory - Asks about switching context without stashing - Wants to clean up old/merged branches and their worktrees - Says phrases like "new worktree", "create worktree", "branch off", "work on something else", "start new work", "parallel work", "separate workspace", "another branch" Use this skill for ANY worktree-related operation, not just when explicitly asking about twig.
Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis accordingly. Activated for "deep search", "multi-source search", or when high-quality research is needed.
Read GitHub repos the RIGHT way - via gitmcp.io instead of raw scraping. Why this beats web search: (1) Semantic search across docs, not just keyword matching, (2) Smart code navigation with accurate file structure - zero hallucinations on repo layout, (3) Proper markdown output optimized for LLMs, not raw HTML/JSON garbage, (4) Aggregates README + /docs + code in one clean interface, (5) Respects rate limits and robots.txt. Stop pasting raw GitHub URLs - use this instead.
Apply plugin knowledge base updates to an existing generated system. Consults the Ars Contexta research graph for methodology improvements, proposes skill upgrades with research justification. Never auto-implements. Triggers on "/upgrade", "upgrade skills", "check for improvements", "update methodology".
Use this skill whenever Claude needs to fetch, read, extract, or analyze content from a web URL. Converts web pages into clean, token-efficient markdown using the markdown.new service instead of fetching raw HTML. Trigger when the user provides a URL and wants its content summarized, quoted, analyzed, compared, extracted, or processed. Also trigger when Claude needs to read documentation, blog posts, articles, wikis, release notes, changelogs, or any web-hosted text content. Even if the user just pastes a URL with no instruction, use this skill. Do NOT use for binary files, authenticated pages, or API endpoints returning JSON/XML.
Teaches learners to extract transferable design lessons from real-world codebases through critical evaluation and systematic exploration. Use when a learner wants to study existing code to learn patterns, architecture, or design decisions—not just understand what it does. Guides through navigation, pattern recognition, critical evaluation (deliberate choice vs. compromise), and lesson extraction. Triggers on phrases like "learn from this codebase", "study how X is implemented", "understand design patterns in Y", or when a learner wants to improve by reading real code.
Use when editing and enhancing images for Xiaohongshu content, improving photo quality with filters and adjustments, creating visually appealing images, or preparing images for carousel posts
Forces exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology. MUST trigger when: (1) any task has failed 2+ times or you're stuck in a loop tweaking the same approach; (2) you're about to say 'I cannot', suggest the user do something manually, or blame the environment without verifying; (3) you catch yourself being passive — not searching, not reading source, not verifying, just waiting for instructions; (4) user expresses frustration in ANY form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', or any similar sentiment even if phrased differently. Also trigger when facing complex multi-step debugging, environment issues, config problems, or deployment failures where giving up early is tempting. Applies to ALL task types: code, config, research, writing, deployment, infrastructure, API integration. Do NOT trigger on first-attempt failures or when a known fix is already executing successfully.