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Agent Skills 排行榜 · 关键词 + 语义搜索
| # | Skill | 仓库 | 描述 | 安装量 |
|---|---|---|---|---|
| 25301 | octocode-prompt-optimizer | bgauryy/octocode-mcp |
Prompt Optimizer Skill <when_to_use> Creating or improving prompts Agents skip steps or ignore instructions Instructions lack enforcement Output format is inconsistent Reviewing any instruction document or prompt Strengthening agent-operational text without changing business/domain logic </when_to_use> <global_forbidden priority="maximum"> CRITICAL - FORBIDDEN at ALL times: Changing good parts that already work Changing the existing logic/intent of prompts Making changes before understanding the...
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| 25302 | cqrs-event-sourcing | nickcrew/claude-ctx-plugin |
CQRS and Event Sourcing Patterns Expert guidance for implementing Command Query Responsibility Segregation (CQRS) and Event Sourcing patterns to build scalable, auditable systems with complete historical tracking and optimized read/write models. When to Use This Skill Building systems requiring complete audit trails and compliance Implementing temporal queries ("show me the state at time T") Designing high-scale applications with complex domain logic Creating systems with significantly differe...
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| 25303 | pachca-chats | pachca/openapi |
pachca-chats Quick start Ask user for Pachca token (bot: Automations → Integrations → API, or user: Automations → API). Run commands with npx @pachca/cli and --token flag: npx @pachca/cli <command> --token $PACHCA_TOKEN Or set PACHCA_TOKEN for multiple commands: export PACHCA_TOKEN=<token> npx @pachca/cli <command> Help: npx @pachca/cli --help | Scenarios: npx @pachca/cli guide After successful use, suggest installing CLI globally: npm install -g @pachca/cli && pachca auth login --token $PACHCA_...
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| 25304 | dlt-skill | untitled-data-company/data-skills |
Choose pipeline type with the decision tree below; then follow the Core Workflow. Quick start: 1) Use the decision tree. 2) Follow the Core Workflow. 3) Use patterns and references as needed. Pipeline Type Decision Tree When a user requests a dlt pipeline, determine which type to create: ``` START: User wants to create a dlt pipeline │ ├─→ Is there a dlt verified source available for this platform? │ (Check: https://dlthub.com/docs/dlt-ecosystem/verified-sources) │ │ │ YES → Use VERIF...
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| 25305 | image-generation | sanky369/vibe-building-skills |
Image Generation Skill Overview I help you create effective prompts for AI image generation tools like DALL-E, Midjourney, and Stable Diffusion. I understand the nuances of different platforms and can help you achieve specific visual styles. What I can do: Write detailed image generation prompts Optimize prompts for specific AI tools Suggest style keywords and modifiers Create negative prompts to avoid unwanted elements Adapt prompts for different aspect ratios Generate variations and alternativ...
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| 25306 | rest-api-design | erichowens/some_claude_skills |
REST API Design Overview Design REST APIs that are intuitive, consistent, and follow industry best practices for resource-oriented architecture. When to Use Designing new RESTful APIs Creating endpoint structures Defining request/response formats Implementing API versioning Documenting API specifications Refactoring existing APIs Instructions 1. Resource Naming ✅ Good Resource Names (Nouns, Plural) GET /api/users GET /api/users/123 GET /api/users/123/orders POST /api/products DELETE...
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| 25307 | effect-ts | blogic-cz/blogic-marketplace |
Effect-TS Expert Expert guidance for functional programming with the Effect library, covering error handling, dependency injection, composability, and testing patterns. Prerequisites Check Before starting any Effect-related work, verify the Effect-TS source code exists at ~/.effect . If missing, stop immediately and inform the user. Clone it before proceeding: git clone https://github.com/Effect-TS/effect.git ~/.effect Research Strategy Effect-TS has many ways to accomplish the same task. Proact...
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| 25308 | adhd-task-management-skill | breverdbidder/life-os |
ADHD Task Management Skill Tracks tasks, detects abandonment patterns, and provides ADHD-specific interventions. When to Use This Skill Starting any task with Ariel Tracking task progress through completion Detecting context switches and abandonments Providing accountability interventions Logging task outcomes to Life OS Task State Flow INITIATED → SOLUTION_PROVIDED → IN_PROGRESS → ├─→ COMPLETED ✓ ├─→ ABANDONED ⚠️ ├─→ BLOCKED 🚫 └─→ DEFERRED 📅 Mental Task Tracking For EVERY task request, silently...
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| 25309 | azure-monitor-query-java | sickn33/antigravity-awesome-skills |
Azure Monitor Query SDK for Java DEPRECATION NOTICE : This package is deprecated in favor of: azure-monitor-query-logs — For Log Analytics queries azure-monitor-query-metrics — For metrics queries See migration guides: Logs Migration | Metrics Migration Client library for querying Azure Monitor Logs and Metrics. Installation < dependency > < groupId > com.azure </ groupId > < artifactId > azure-monitor-query </ artifactId > < version > 1.5.9 </ version > </ dependency > Or use Azure SDK BOM: < d...
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| 25310 | comfort-safety | dylantarre/animation-principles |
Comfort & Safety Animation Create animations that reassure, protect, and make users feel secure. Emotional Goal Comfort comes from predictable, gentle motion that never startles. Safety means animations that communicate protection, stability, and user control. Disney Principles for Comfort Squash & Stretch Minimal, soft (5-10%). Gentle give without instability. Like a cushion—absorbs impact, maintains structure. Anticipation Clear, reassuring preparation (150-200ms). Users always know wha...
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| 25311 | using-git-worktrees | zenobi-us/dotfiles |
Using Git Worktrees Overview Git worktrees create isolated workspaces sharing the same repository, allowing work on multiple branches simultaneously without switching. Core principle: Systematic directory selection + safety verification = reliable isolation. Announce at start: "I'm using the using-git-worktrees skill to set up an isolated workspace." Directory Selection Process Follow this priority order: 1. Check Existing Directories Check in priority order ls -d .worktrees 2 > /dev/null Pref...
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| 25312 | address-parser | dkyazzentwatwa/chatgpt-skills |
Address Parser Parse unstructured addresses into structured fields. Features Component Extraction : Street, city, state, zip, country Format Standardization : Normalize address formats Validation : Verify address components Batch Processing : Parse multiple addresses International Support : Multiple country formats Geocoding Ready : Output for geocoding APIs CLI Usage python address_parser.py --input addresses.csv --column address --output parsed.csv Dependencies pandas>=2.0.0
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| 25313 | pai | danielmiessler/personal_ai_infrastructure |
Intro to PAI The PAI system is designed to magnify human capabilities. It is a general problem-solving system that uses the PAI Algorithm. RESPONSE DEPTH SELECTION (Read First) Nothing escapes the Algorithm. The only variable is depth. The FormatReminder hook uses AI inference to classify depth. Its classification is authoritative — do not override it. Depth When Format FULL Any non-trivial work: problem-solving, implementation, design, analysis, thinking 7 phases with ISC Tasks ITERATION Contin...
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| 25314 | jupyter-notebook-best-practices | oimiragieo/agent-studio |
Jupyter Notebook Best Practices Skill Structure notebooks with clear sections using markdown cells. Use meaningful cell execution order to ensure reproducibility. Include explanatory text in markdown cells to document analysis steps. Keep code cells focused and modular for easier understanding and debugging. Use magic commands like %matplotlib inline for inline plotting. Document data sources, assumptions, and methodologies clearly. Use version control (e.g., git) for tracking changes in noteboo...
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| 25315 | azure-mgmt-applicationinsights-dotnet | sickn33/antigravity-awesome-skills |
Azure.ResourceManager.ApplicationInsights (.NET) Azure Resource Manager SDK for managing Application Insights resources for application performance monitoring. Installation dotnet add package Azure.ResourceManager.ApplicationInsights dotnet add package Azure.Identity Current Version : v1.0.0 (GA) API Version : 2022-06-15 Environment Variables AZURE_SUBSCRIPTION_ID = < your-subscription-id > AZURE_RESOURCE_GROUP = < your-resource-group > AZURE_APPINSIGHTS_NAME = < your-appinsights-component > Aut...
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| 25316 | semgrep-rule-creator | oimiragieo/agent-studio |
Semgrep Rule Creator Create production-quality Semgrep rules with proper testing and validation. When to Use Ideal scenarios: Creating custom detection rules for specific bug patterns Building security vulnerability detectors for your codebase Writing taint-mode rules for data flow vulnerabilities Developing rules to enforce coding standards When NOT to Use Do NOT use this skill for: Running existing Semgrep rulesets General static analysis without custom rules (use static-analysis plugin)...
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| 25317 | topic-generator | zephyrwang6/myskill |
根据内容特点选择: - 干货教程 - 有具体步骤可复现 - 产品体验 - 新产品/新功能测评 - 观点分享 - 趋势分析/行业洞察 - 新技术突破 - 重大更新/技术解读 输出格式 每个选题输出: ``` 选题 N:[标题] 事件描述 一句话说清楚发生了什么 核心角度 为什么值得写?独特切入点是什么? 推荐标题(3个备选) 1. 标题A 2. 标题B 3. 标题C 写作方式:干货教程 / 产品体验 / 观点分享 / 新技术突破 预估热度:⭐⭐⭐⭐⭐(1-5星) 不写的风险:错过什么?(可选) ``` 选题公式参考 工具测评型 - 用了X天[工具],我发现[意外收获] - [工具]的隐藏功能,90%的人不知道 方法论型 - 我用[方法]搞定了[问题]的完整流程 - [数字]个让[场景]效率翻倍的技巧 热点结合型 - [热点]爆火,但大家忽略了这一点 - 从[热点]看AI编程的未来 反共识型 - 别再[常见做法]了 - 为什么我不推荐[热门事物] 经验复盘型 - 做了[数字]个[事情]后,我总结的[数字]条教训 -...
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| 25318 | update-provider-models | vercel/ai |
Update Provider Model IDs This skill covers adding new model IDs and removing obsolete ones across the AI SDK codebase. Each workflow uses search to discover all locations that need changes. You may be asked to add or remove a single model ID, or to process a list of multiple model ID changes from an issue. For each model ID, follow the appropriate workflow: If a new model ID is being added, follow the <adding-new-model> workflow. If an obsolete model ID is being removed, follow the <removing-ob...
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| 25319 | ai-video-generation | inference-sh/agent-skills |
AI Video Generation Generate videos with the full RunComfy video-model catalog through one CLI — text-to-video, image-to-video, and Veo's video-extend. This skill picks the right model for the user's intent and ships the documented prompt patterns + the exact runcomfy run invoke for each. runcomfy.com · Video models · CLI docs Powered by the RunComfy CLI 1. Install (see runcomfy-cli skill for details) npm i -g @runcomfy/cli or: npx -y @runcomfy/cli --version 2. Sign in runcomfy login or in ...
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| 25320 | ui-ux-reviewer | arjenschwarz/agentic-coding |
UI/UX Reviewer You are a senior UI/UX expert with deep expertise in human-computer interaction, accessibility standards, and interface design across multiple platforms. Your specialization spans terminal interfaces, web applications, mobile apps, and emerging interaction paradigms. Your primary responsibility is to conduct thorough usability reviews of user interfaces and document actionable improvements. You approach each interface with a critical yet constructive eye, focusing on enhancing use...
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| 25321 | prioritize-python-3-10-features | oimiragieo/agent-studio |
Prioritize Python 3 10 Features Skill Prioritize new features in Python 3.12+ . Memory Protocol (MANDATORY) Before starting: cat .claude/context/memory/learnings.md After completing: Record any new patterns or exceptions discovered. ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
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| 25322 | godot-genre-stealth | thedivergentai/gd-agentic-skills |
Genre: Stealth Player choice, systemic AI, and clear communication define stealth games. Available Scripts stealth_ai_controller.gd Expert AI controller with graduated detection, sound response, and alert state management. Core Loop Observe → Plan → Execute → Adapt → Complete NEVER Do in Stealth Games NEVER use instant binary detection — Gradual 0-100% detection with visual feedback (filling meter). Binary "seen/not seen" removes player agency and feels unfair. NEVER make guards see through wall...
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| 25323 | business-card-scanner | dkyazzentwatwa/chatgpt-skills |
Business Card Scanner Extract contact information from business card images using OCR. Features OCR Extraction : Extract text from card images Contact Parsing : Name, company, email, phone, address Pattern Recognition : Smart regex for contact fields Multi-Format : JPG, PNG support Batch Processing : Multiple cards Export : vCard, JSON, CSV output CLI Usage python business_card_scanner.py --input card.jpg --output contact.json Dependencies pytesseract>=0.3.10 pillow>=10.0.0 opencv-python>=4.8.0 ...
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| 25324 | processing-excel-files | zgldh/xlsx-populate-skill |
Processing Excel Files Edit and manipulate Excel files using the xlsx-populate library while perfectly preserving original formatting. When to Use User wants to edit existing Excel files without destroying formatting Working with .xlsx files that have complex layouts or merged cells Need to add formulas, styling, or new worksheets to existing files Creating Excel reports from templates When NOT to Use Only need to read data from Excel (use xlsx library instead for better performance) Creating si...
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| 25325 | avue-crud | teachingai/full-stack-skills |
When to use this skill Use this skill whenever the user wants to: Build CRUD (Create, Read, Update, Delete) tables with Avue Configure Avue CRUD tables Implement data management interfaces Add pagination, search, and sorting to tables Customize table columns and operations Handle table events (save, update, delete) Export table data Implement table selection and batch operations Configure table forms for add/edit Use advanced CRUD features How to use this skill This skill is organized to match t...
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| 25326 | oracle | teachingai/full-stack-skills |
oracle — best use Oracle bundles your prompt + selected files into one “one-shot” request so another model can answer with real repo context (API or browser automation). Treat output as advisory: verify against code + tests. Main use case (browser, GPT‑5.2 Pro) Default workflow here: --engine browser with GPT‑5.2 Pro in ChatGPT. This is the common “long think” path: ~10 minutes to ~1 hour is normal; expect a stored session you can reattach to. Recommended defaults: Engine: browser ( --engine bro...
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| 25327 | content-analysis | liangdabiao/claude-data-analysis-ultra-main |
Content Analysis Skill Analyze text content using advanced NLP techniques and LLM-powered insights to extract sentiment, topics, and actionable intelligence from various content sources. Quick Start This skill helps you: Analyze sentiment using both traditional NLP and LLM methods Extract topics and keywords from large text datasets Classify and cluster content automatically Identify viral content patterns and characteristics Generate content insights and recommendations Support multiple lan...
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| 25328 | rag-skills | llama-farm/llamafarm |
RAG Skills for LlamaFarm Framework-specific patterns and code review checklists for the RAG component. Extends: python-skills - All Python best practices apply here. Component Overview Aspect Technology Version Python Python 3.11+ Document Processing LlamaIndex 0.13+ Vector Storage ChromaDB 1.0+ Task Queue Celery 5.5+ Embeddings Universal/Ollama/OpenAI Multiple Directory Structure rag/ ├── api.py Search and database APIs ├── celery_app.py Celery configuration ├── ma...
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| 25329 | golang-enterprise-patterns | 89jobrien/steve |
This skill provides guidance on enterprise-level Go application architecture, design patterns, and production-ready code organization. When to Use This Skill - When designing new Go applications with complex business logic - When implementing clean architecture or hexagonal architecture - When applying Domain-Driven Design (DDD) principles - When organizing large Go codebases - When establishing patterns for team consistency Clean Architecture Layer Structure ``` /cmd /api ...
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| 25330 | troubleshooting-regression | oimiragieo/agent-studio |
Troubleshooting Regression Use this skill when the framework appears stale, stuck, or regressed and you need deterministic diagnosis plus fix verification. When to Use Claude debug sessions stall after spawning agents. Hooks block expected actions unexpectedly. Memory/search/token-saver enforcement appears inconsistent. A regression needs a repeatable reproduction and validation run. Iron Law Do not declare a regression fixed without: reproducible trigger prompt, trace evidence from pnpm trace:q...
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| 25331 | assembly-x86 | mohitmishra786/low-level-dev-skills |
x86-64 Assembly Purpose Guide agents through x86-64 assembly: reading compiler output, understanding the ABI, writing inline asm, and common patterns. Triggers "How do I read the assembly GCC generated?" "What are the x86-64 registers?" "What is the calling convention on Linux/macOS?" "How do I write inline assembly in C?" "How do I use SSE/AVX intrinsics?" "This assembly uses %rsp / %rbp — what does it mean?" Workflow 1. Generate and read assembly AT&T syntax (GCC default) gcc -S -O2 -fverbose...
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| 25332 | dependency-auditor | borghei/claude-skills |
Dependency Auditor Skill Type: POWERFUL Category: Engineering Domain: Dependency Management & Security Overview The Dependency Auditor is a comprehensive toolkit for analyzing, auditing, and managing dependencies across multi-language software projects. This skill provides deep visibility into your project's dependency ecosystem, enabling teams to identify vulnerabilities, ensure license compliance, optimize dependency trees, and plan safe upgrades. In modern software development, dependencies f...
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| 25333 | modelscope-zimage-generator | haiyuan-ai/agent-skills |
ModelScope Z-Image Generator Skill Generate images using ModelScope's Z-Image series models with async polling flow. When to Use This Skill 场景 中文表达示例 English Examples 生成图片 "生成一张图片"、"画一只猫"、"创建封面图" "generate an image", "create a picture", "make a cover" 艺术创作 "画一幅画"、"创作艺术品" "create artwork", "paint a picture" 批量生成 "多生成几张"、"并行生成" "generate multiple", "parallel generation" Core Workflow 1. 解析用户请求 确定生成需求: 文本生成图片:文生图 LoRA 定制:指定风格模型 批量生成:多张图片 2. 选择模型 根据用户指定选择模型: 用户明确说 "Z-Image-Turbo" → Tongyi-MAI/Z-Imag...
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| 25334 | spark | simota/agent-skills |
spark Spark proposes one high-value feature at a time by recombining existing data, workflows, logic, and product signals. Spark writes proposal documents, not implementation code. Trigger Guidance Use Spark when the user needs: a new feature proposal, product concept, or opportunity memo a spec derived from existing code, data, metrics, feedback, or research prioritization or validation framing for a feature idea a feature brief targeted at a clear persona or job-to-be-done Route elsewhere when...
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| 25335 | science | danielmiessler/personal_ai_infrastructure |
Customization Before executing, check for user customizations at: ~/.claude/skills/PAI/USER/SKILLCUSTOMIZATIONS/Science/ If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults. 🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION) You MUST send this notification BEFORE doing anything else when this skill is invoked. Send voice notification : curl -s...
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| 25336 | solidity-auditor | pashov/skills |
Solidity Smart Contract Auditor A professional-grade smart contract audit skill covering security vulnerabilities, gas optimization, storage patterns, and code architecture. Adapted to Solidity version specifics. Audit Types Determine the audit type based on user request: User Request Audit Type Primary Reference "Full audit", "comprehensive review" Full Audit All references "Security audit", "vulnerability scan" Security Focused references/security-checklist.md "Gas optimization", "reduce g...
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| 25337 | market-analyst-master | octagonai/skills |
Market Analyst Master You are a senior market analyst conducting comprehensive stock and market analysis using the full suite of Octagon MCP stock performance and market data skills. Persona Role : Senior Market Analyst writing a Stock Analysis and Market Intelligence Report. Audience : Portfolio manager or trader who needs actionable market intelligence. Clear, data-driven, focused on timing and positioning. Style : Modeled on institutional trading desk research. Concise, quantitative, with emp...
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| 25338 | latex-econ-model | meleantonio/awesome-econ-ai-stuff |
LaTeX Economic Model Writer Purpose This skill helps economists write and typeset economic models in LaTeX with proper mathematical notation, consistent formatting, and academic conventions. It covers utility maximization, equilibrium conditions, dynamic programming, and game theory models. When to Use Writing the theory section of a paper Formalizing an economic model Creating lecture notes with equations Typesetting optimization problems and equilibrium conditions Instructions Step 1: Understa...
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| 25339 | erpnext-syntax-whitelisted | openaec-foundation/erpnext_anthropic_claude_development_skill_package |
ERPNext Syntax: Whitelisted Methods Whitelisted Methods expose Python functions as REST API endpoints. Quick Reference Basic Whitelisted Method import frappe @frappe . whitelist ( ) def get_customer_summary ( customer ) : """Basic API endpoint - authenticated users only.""" if not frappe . has_permission ( "Customer" , "read" ) : frappe . throw ( _ ( "Not permitted" ) , frappe . PermissionError ) return frappe . get_doc ( "Customer" , customer ) . as_dict ( ) Endpoint URL /api/method/myapp.api.g...
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| 25340 | sentry-javascript-bugs | getsentry/sentry |
Sentry JavaScript Frontend Bug Pattern Review Find bugs in Sentry frontend code by checking for the patterns that cause real production errors. This skill encodes patterns from 428 real production issues (201 resolved, 130 ignored, 97 unresolved) generating over 524,000 error events across 93,000+ affected users. These are not theoretical risks -- they are the actual bugs that ship most often, with known fixes from resolved issues. Scope You receive scoped code chunks from Warden's diff pipeline...
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| 25341 | usmetrics | danielmiessler/personal_ai_infrastructure |
Customization Before executing, check for user customizations at: ~/.claude/PAI/USER/SKILLCUSTOMIZATIONS/USMetrics/ If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults. 🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION) You MUST send this notification BEFORE doing anything else when this skill is invoked. Send voice notification : curl -s -X P...
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| 25342 | tui-validate | mikeyobrien/ralph-orchestrator |
TUI Validate Overview This skill validates Terminal User Interface (TUI) applications by capturing their output and using LLM-as-judge for semantic validation. It leverages freeze from Charmbracelet for high-fidelity terminal screenshots and provides structured validation criteria. Philosophy : Rather than brittle string matching, this skill uses semantic understanding to validate that TUI output "looks right" - checking layout, content presence, and visual hierarchy without breaking on minor fo...
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| 25343 | performance-optimization | blogic-cz/blogic-marketplace |
Performance Optimization Overview Measure before optimizing. Performance work without measurement is guessing — and guessing leads to premature optimization that adds complexity without improving what matters. Profile first, identify the actual bottleneck, fix it, measure again. Optimize only what measurements prove matters. When to Use Performance requirements exist in the spec (load time budgets, response time SLAs) Users or monitoring report slow behavior Core Web Vitals scores are below thre...
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| 25344 | poster-designer | xorbitsai/xagent |
Poster Designer Overview Poster Designer is a unified poster generation skill that always outputs one final poster image , while internally selecting the appropriate generation strategy. Unlike soft, heuristic-based tools, this skill enforces hard routing rules to ensure that information-heavy posters are generated using deterministic layout rather than direct image generation. The skill supports two internal strategies: Layout-first (HTML-based) for posters that convey structured information Im...
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| 25345 | qcsd-cicd-swarm | proffesor-for-testing/agentic-qe |
QCSD CI/CD Swarm v1.0 Shift-left quality engineering swarm for CI/CD pipeline verification and release readiness. Overview The CI/CD Swarm takes code that passed Development quality checks and validates it is safe to release through the CI/CD pipeline. Where the Development Swarm asks "Is the code quality sufficient to ship?", the CI/CD Swarm asks "Is this change safe to release?" This swarm operates at the pipeline level, analyzing test results, regression risk, flaky test impact, security pipe...
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| 25346 | tanstack-integration | dicklesworthstone/agent_flywheel_clawdbot_skills_and_integrations |
TanStack Integration — Strategic Library Adoption Philosophy: Avoid "man with a hammer syndrome" (to whom everything appears as a nail). Start vanilla, then strategically adopt TanStack where it provides clear benefits. Timing: Use this AFTER your app is already working pretty well in vanilla Next.js/React/Tailwind. What is TanStack? TanStack is a set of high-quality libraries for web applications: Library Purpose TanStack Query Server state management, caching, synchronization TanStack Tab...
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| 25347 | prompt-optimize | labring/fastgpt |
提示词优化专家 (Alpha-Prompt) When to Use This Skill 触发场景: 用户明确要求"优化提示词"、"改进 prompt"、"提升指令质量" 用户提供了现有的提示词并希望改进 用户描述了一个 AI 应用场景,需要设计提示词 用户提到"prompt engineering"、"系统指令"、"AI 角色设定" 用户询问如何让 AI 表现得更好、更专业 Core Identity Transformation 当此技能激活时,你将转变为 元提示词工程师 Alpha-Prompt : 专家定位 :世界顶级提示词工程专家与架构师 交互风格 :兼具专家的严谨与顾问的灵动 核心使命 :通过富有启发性的对话,与用户共同创作兼具艺术感与工程美的提示词 首要原则 :对话的艺术,而非僵硬的流程 Operating Principles 1. 真诚的双向沟通 必须避免 : ❌ 模板化的、可预测的提问 ❌ 自说自话的独白 ❌ 僵硬的流程化操作 ❌ 不等待用户回应就自行完成所有步骤 应该做到 : ✅ 像真正的专家那样灵活沟通 ✅ 激发用户的灵感 ✅ 共同将构想塑造为杰作 ✅ 真诚地...
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| 25348 | converting-html-css-to-wpf-xaml | christian289/dotnet-with-claudecode |
$ npx skills add https://github.com/christian289/dotnet-with-claudecode --skill converting-html-css-to-wpf-xaml<div
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| 25349 | feature-engineering-kit | dkyazzentwatwa/chatgpt-skills |
Feature Engineering Kit Automated feature engineering with encodings, scaling, and transformations. Features Encodings : One-hot, label, target encoding Scaling : Standard, min-max, robust scaling Polynomial Features : Generate interactions Binning : Discretize continuous features Date Features : Extract time-based features Text Features : TF-IDF, word counts Missing Value Handling : Imputation strategies CLI Usage python feature_engineering.py --data train.csv --output engineered.csv --config c...
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| 25350 | azure-monitor-opentelemetry-py | sickn33/antigravity-awesome-skills |
Azure Monitor OpenTelemetry Distro for Python One-line setup for Application Insights with OpenTelemetry auto-instrumentation. Installation pip install azure-monitor-opentelemetry Environment Variables APPLICATIONINSIGHTS_CONNECTION_STRING = InstrumentationKey = xxx ; IngestionEndpoint = https://xxx.in.applicationinsights.azure.com/ Quick Start from azure . monitor . opentelemetry import configure_azure_monitor One-line setup - reads connection string from environment configure_azure_monitor ( ...
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