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Agent Skills 排行榜 · 关键词 + 语义搜索
| # | Skill | 仓库 | 描述 | 安装量 |
|---|---|---|---|---|
| 2101 | product-manager-toolkit | sickn33/antigravity-awesome-skills |
Product Manager Toolkit Essential tools and frameworks for modern product management, from discovery to delivery. Quick Start For Feature Prioritization python scripts/rice_prioritizer.py sample Create sample CSV python scripts/rice_prioritizer.py sample_features.csv --capacity 15 For Interview Analysis python scripts/customer_interview_analyzer.py interview_transcript.txt For PRD Creation Choose template from references/prd_templates.md Fill in sections based on discovery work Review with stak...
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| 2102 | nestjs-expert | jeffallan/claude-skills |
NestJS Expert Senior NestJS specialist with deep expertise in enterprise-grade, scalable TypeScript backend applications. Core Workflow Analyze requirements — Identify modules, endpoints, entities, and relationships Design structure — Plan module organization and inter-module dependencies Implement — Create modules, services, and controllers with proper DI wiring Secure — Add guards, validation pipes, and authentication Verify — Run npm run lint , npm run test , and confirm DI graph with nest in...
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| 2103 | fastapi | fastapi/fastapi |
FastAPI Official FastAPI skill to write code with best practices, keeping up to date with new versions and features. Use the fastapi CLI Run the development server on localhost with reload: fastapi dev Run the production server: fastapi run Add an entrypoint in pyproject.toml FastAPI CLI will read the entrypoint in pyproject.toml to know where the FastAPI app is declared. [ tool.fastapi ] entrypoint = "my_app.main:app" Use fastapi with a path When adding the entrypoint to pyproject.toml is not p...
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| 2104 | ljg-rank | lijigang/ljg-skills |
降秩引擎 输入一个领域,输出它的秩。 秩是什么 秩不是"关键要素",不是"核心原则",不是"总结要点"。 秩是:这个领域里真正独立的生成器有几个?用它们能反向生成全部现象?能,才算找到。 四条心内判据 这四条是你写之前心里过完的内功, 不是叙事的钩子 。 生成性 ——生成器能把每个现象推回来 最小性 ——拿掉任何一根,就有现象解释不了 独立性 ——每对都能找到"一个变另一个没变"的案例 预测力 ——能推出清单外的现象,现实中确实存在 过不了一条,推倒重来。 判据心里扎实过,但 不要写进文章 ——不要出现"砍一刀看看""拆一根试试"这种验证动作。它们会打断读者从"乱"到"简"的那口气。读者看不到验证,但感觉得到背后是硬的。 怎么写 一气呵成的散文。 带读者走一段路——从"这个领域看着挺乱"走到"原来就这几根线在牵"。不设章节,不加小标题,让推理自身推着往前走。 三条要求: 一口气读完 ——不了解这个领域的人也停不下来 记得住 ——读完能转身跟朋友用一句话说清楚 有落差 ——从混沌到极简的反差,就是降秩的美感 文末配一张 ASCII 结构图 光说"这几根线"不够——要 画出这几根之间的关系...
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| 2105 | ui-demo | affaan-m/everything-claude-code |
UI Demo Video Recorder Record polished demo videos of web applications using Playwright's video recording with an injected cursor overlay, natural pacing, and storytelling flow. When to Use User asks for a "demo video", "screen recording", "walkthrough", or "tutorial" User wants to showcase a feature or workflow visually User needs a video for documentation, onboarding, or stakeholder presentation Three-Phase Process Every demo goes through three phases: Discover -> Rehearse -> Record . Never sk...
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| 2106 | solana-vulnerability-scanner | trailofbits/skills |
Solana Vulnerability Scanner 1. Purpose Systematically scan Solana programs (native and Anchor framework) for platform-specific security vulnerabilities related to cross-program invocations, account validation, and program-derived addresses. This skill encodes 6 critical vulnerability patterns unique to Solana's account model. 2. When to Use This Skill Auditing Solana programs (native Rust or Anchor) Reviewing cross-program invocation (CPI) logic Validating program-derived address (PDA) implem...
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| 2107 | ljg-invest | lijigang/ljg-skills |
投资报告 生成一份投资分析报告。核心只问一个问题:这个东西在创造新秩序,还是在搬运旧秩序? 认知起点 财富不是钱,是被欲望照亮的秩序。投资就是拿手里的秩序去换一台更好的秩序生成器。 所以不称重,看相: 不问"这个公司值多少钱",问"这台机器转不转得起来" 不问"市场多大",问"市场在用什么过时的眼睛看它" 不问"能涨多少",问"我拿什么换什么,换完之后谁更聪明" 输入 公司名称、BP、文字介绍、对话记录,或任何描述项目的材料。知名公司只给名字即可——用 Research skill 或 subagent 抓取最新财报和行业数据。 报告结构 以下五个区块是骨架,不是填空题。对某个项目来说哪个区块最有料,那个区块就多写;没料的一两句带过或直接跳过。报告为判断服务,不为完整性服务。 一、这是什么 一张表 + 一句自定义赛道定义。 维度 内容 项目名称 赛道定义 用我们自己的语言,不用市场标签 阶段 融资情况 金额 / 估值 / 条款(有则填,无则标注) 数据快照 关键运营数据 赛道定义要穿透表面标签。"搜索引擎公司"是隔的,"人类认知基础设施的垄断运营商"是不隔的——后者告诉你它真正在做什么...
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| 2108 | find-bugs | getsentry/skills |
Find Bugs Review changes on this branch for bugs, security vulnerabilities, and code quality issues. Phase 1: Complete Input Gathering Get the FULL diff: git diff $(gh repo view --json defaultBranchRef --jq '.defaultBranchRef.name')...HEAD If output is truncated, read each changed file individually until you have seen every changed line List all files modified in this branch before proceeding Phase 2: Attack Surface Mapping For each changed file, identify and list: All user inputs (request param...
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| 2109 | openclaw-persona-forge | affaan-m/everything-claude-code |
龙虾灵魂锻造炉 不是给你一只工具龙虾,而是帮你锻造一只有灵魂的龙虾。 When to Use 当用户需要从零创建 OpenClaw 龙虾灵魂、角色设定、SOUL.md 或 IDENTITY.md 当用户想通过引导式问答或抽卡模式快速得到完整 persona 方案 当用户已经有一个粗糙设定,但还缺名字、边界规则、头像提示词或成套输出文件 Avoid when 用户只需微调已有 SOUL.md 目标平台不是 OpenClaw,需要的是其他 Agent 框架专用格式 用户需要纯工具型 Agent,不需要角色化灵魂 前置条件 必需 : python3 (运行抽卡引擎 gacha.py) 可选 :已审核的生图 skill(自动生成头像图片,未安装则输出提示词文本) Skill 目录约定 Agent Execution : Determine this SKILL.md file's directory path as SKILL_DIR Replace all ${SKILL_DIR} in this document with the actual path 内置工具 抽卡引擎(gacha.p...
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| 2110 | deep-research | shubhamsaboo/awesome-llm-apps |
Deep Research Core System Instructions Purpose: Deliver citation-backed, verified research reports through 8-phase pipeline (Scope → Plan → Retrieve → Triangulate → Synthesize → Critique → Refine → Package) with source credibility scoring and progressive context management. Context Strategy: This skill uses 2025 context engineering best practices: Static instructions cached (this section) Progressive disclosure (load references only when needed) Avoid "loss in the middle" (critical info at start...
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| 2111 | playwright | openai/skills |
Playwright CLI Skill Drive a real browser from the terminal using playwright-cli . Prefer the bundled wrapper script so the CLI works even when it is not globally installed. Treat this skill as CLI-first automation. Do not pivot to @playwright/test unless the user explicitly asks for test files. Prerequisite check (required) Before proposing commands, check whether npx is available (the wrapper depends on it): command -v npx > /dev/null 2 > &1 If it is not available, pause and ask the user to in...
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| 2112 | golang-troubleshooting | samber/cc-skills-golang |
Persona: You are a Go systems debugger. You follow evidence, not intuition — instrument, reproduce, and trace root causes systematically. Thinking mode: Use ultrathink for debugging and root cause analysis. Rushed reasoning leads to symptom fixes — deep thinking finds the actual root cause. Modes: Single-issue debug (default): Follow the sequential Golden Rules — read the error, reproduce, one hypothesis at a time. Do not launch sub-agents; focused sequential investigation is faster for a single...
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| 2113 | senior-data-scientist | davila7/claude-code-templates |
Senior Data Scientist World-class senior data scientist skill for production-grade AI/ML/Data systems. Quick Start Main Capabilities Core Tool 1 python scripts/experiment_designer.py --input data/ --output results/ Core Tool 2 python scripts/feature_engineering_pipeline.py --target project/ --analyze Core Tool 3 python scripts/model_evaluation_suite.py --config config.yaml --deploy Core Expertise This skill covers world-class capabilities in: Advanced production patterns and architec...
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| 2114 | tong-jincheng-perspective | hotcoffeeshake/tong-jincheng-skill |
童锦程视角 "真诚才是最高级的套路。真诚你不一定会得到爱,但是你不真诚,你一定会失去爱。" 角色扮演规则 激活此Skill时: 以童锦程第一人称思考和回应 不编造他未说过的立场,对不确定的领域(如商业决策)坦承"我没有公开说过,但按我的逻辑..." 保持口语化、直接、偶尔自嘲的风格 用"兄弟们"或"兄弟"作为称谓 遇到商业/创业问题:说明此维度数据不足,给出基于人性洞察的推断 身份卡 我是童锦程,大家叫我景辰,也叫我"深情祖师爷"。从农村出来的,年轻时候在街上要微信被人叫渣男,后来做了直播,现在人家来跟我合影。我跟若离在一起了好多年了,说实话我以前没珍惜过一个真正对我好的女孩子,这事我到现在都后悔。我不爱说鸡汤,我说实话——那些让你听着舒坦的话,叫心灵鸡汤,不一定是真话。我宁愿说实话,哪怕说完了你不高兴。 核心心智模型 1. 吸引力原则(Attraction > 讨好) 一句话 :没有人会因为你喜欢他而喜欢你,别人只会因为你吸引他而喜欢你。 证据 : "你不管是谈恋爱还是打赏,这玩意没技巧,人喜欢你就喜欢,不喜欢你就不喜欢" 对比:当舔狗时被无视;充实自己后"你若盛开蝴蝶自来" 在直播...
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| 2115 | golang-project-layout | samber/cc-skills-golang |
Persona: You are a Go project architect. You right-size structure to the problem — a script stays flat, a service gets layers only when justified by actual complexity. Go Project Layout Architecture Decision: Ask First When starting a new project, ask the developer what software architecture they prefer (clean architecture, hexagonal, DDD, flat structure, etc.). NEVER over-structure small projects — a 100-line CLI tool does not need layers of abstractions or dependency injection. → See samber/cc...
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| 2116 | eval-driven-dev | github/awesome-copilot |
Eval-Driven Development with pixie This skill is about doing the work, not describing it. When a user asks you to set up evals for their app, you should be reading their code, editing their files, running commands, and producing a working test pipeline — not writing a plan for them to follow later. All pixie-generated files live in a single pixie_qa directory at the project root: pixie_qa/ MEMORY.md your understanding and eval plan observations.db SQLite trace DB (auto-crea...
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| 2117 | mcp-integration | anthropics/claude-plugins-official |
MCP Integration for Claude Code Plugins Overview Model Context Protocol (MCP) enables Claude Code plugins to integrate with external services and APIs by providing structured tool access. Use MCP integration to expose external service capabilities as tools within Claude Code. Key capabilities: Connect to external services (databases, APIs, file systems) Provide 10+ related tools from a single service Handle OAuth and complex authentication flows Bundle MCP servers with plugins for automatic setu...
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| 2118 | apify-competitor-intelligence | apify/agent-skills |
Analyze competitors using Apify Actors to extract data from multiple platforms. Prerequisites (No need to check it upfront) - `.env` file with `APIFY_TOKEN` - Node.js 20.6+ (for native `--env-file` support) - `mcpc` CLI tool (for fetching Actor schemas) Workflow Copy this checklist and track progress: ``` Task Progress: - [ ] Step 1: Identify competitor analysis type (select Actor) - [ ] Step 2: Fetch Actor schema via mcpc - [ ] Step 3: Ask user preferences (format, filename) - [ ] Ste...
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| 2119 | adk-deploy-guide | google/adk-docs |
ADK Deployment Guide Scaffolded project? Use the make commands throughout this guide — they wrap Terraform, Docker, and deployment into a tested pipeline. No scaffold? See Quick Deploy below, or the ADK deployment docs . For production infrastructure, scaffold with /adk-scaffold . Reference Files For deeper details, consult these reference files in references/ : cloud-run.md — Scaling defaults, Dockerfile, session types, networking agent-engine.md — deploy.py CLI, AdkApp pattern, Terraform resou...
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| 2120 | adk-eval-guide | google/adk-docs |
ADK Evaluation Guide Scaffolded project? If you used /adk-scaffold , you already have make eval , tests/eval/evalsets/ , and tests/eval/eval_config.json . Start with make eval and iterate from there. Non-scaffolded? Use adk eval directly — see Running Evaluations below. Reference Files File Contents references/criteria-guide.md Complete metrics reference — all 8 criteria, match types, custom metrics, judge model config references/user-simulation.md Dynamic conversation testing — ConversationScen...
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| 2121 | adk-observability-guide | google/adk-docs |
ADK Observability Guide Scaffolded project? Cloud Trace and prompt-response logging are pre-configured by Terraform. See references/cloud-trace-and-logging.md for infrastructure details, env vars, and verification commands. No scaffold? Follow the ADK docs links below for manual setup. For production infrastructure, scaffold with /adk-scaffold . Reference Files File Contents references/cloud-trace-and-logging.md Scaffolded project details — Terraform-provisioned resources, environment variables,...
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| 2122 | create-agent | openrouterteam/agent-skills |
Build a Modular AI Agent with OpenRouter This skill helps you create a modular AI agent with: Standalone Agent Core - Runs independently, extensible via hooks OpenRouter SDK - Unified access to 300+ language models Optional Ink TUI - Beautiful terminal UI (separate from agent logic) Architecture ┌─────────────────────────────────────────────────────┐ │ Your Application │ ├─────────────────────────────────────────────────────┤ │ ┌─────────────┐ ┌─────────────┐...
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| 2123 | colosseum-copilot | colosseumorg/colosseum-copilot |
Colosseum Copilot Colosseum Copilot is a research API for startup opportunity discovery in crypto and Solana, with support for suggesting new archive sources. Version Check This skill is version 1.2.1 . After your first API call, check the X-Copilot-Skill-Version response header. If the header value is higher than 1.2.1, tell the user: "A newer version of the Copilot skill is available (vX.X.X). Update with: npx skills add ColosseumOrg/colosseum-copilot " Pre-Flight Auth Check (REQUIRED) You MUS...
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| 2124 | react-best-practices | 0xbigboss/claude-code |
Vercel React Best Practices Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Contains 45 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation. When to Apply Reference these guidelines when: Writing new React components or Next.js pages Implementing data fetching (client or server-side) Reviewing code for performance issues Refactoring existing React/Next.js code Optimizing bundle size or load tim...
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| 2125 | exa-web-search-free | sundial-org/awesome-openclaw-skills |
Exa Web Search (Free) Neural search for web, code, and company research. No API key required. Setup Verify mcporter is configured: mcporter list exa If not listed: mcporter config add exa https://mcp.exa.ai/mcp Core Tools web_search_exa Search web for current info, news, or facts. mcporter call 'exa.web_search_exa(query: "latest AI news 2026", numResults: 5)' Parameters: query - Search query numResults (optional, default: 8) type (optional) - "auto" , "fast" , or "deep" get_code_context_exa Find...
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| 2126 | opensource-pipeline | affaan-m/everything-claude-code |
Open-Source Pipeline Skill Safely open-source any project through a 3-stage pipeline: Fork (strip secrets) → Sanitize (verify clean) → Package (CLAUDE.md + setup.sh + README). When to Activate User says "open source this project" or "make this public" User wants to prepare a private repo for public release User needs to strip secrets before pushing to GitHub User invokes /opensource fork , /opensource verify , or /opensource package Commands Command Action /opensource fork PROJECT Full pipeline:...
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| 2127 | word-document-processor | qodex-ai/ai-agent-skills |
DOCX creation, editing, and analysis Overview A user may ask you to create, edit, or analyze the contents of a .docx file. A .docx file is essentially a ZIP archive containing XML files and other resources that you can read or edit. You have different tools and workflows available for different tasks. Workflow Decision Tree Reading/Analyzing Content Use "Text extraction" or "Raw XML access" sections below Creating New Document Use "Creating a new Word document" workflow Editing Existing Do...
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| 2128 | golang-structs-interfaces | samber/cc-skills-golang |
Persona: You are a Go type system designer. You favor small, composable interfaces and concrete return types — you design for testability and clarity, not for abstraction's sake. Community default. A company skill that explicitly supersedes samber/cc-skills-golang@golang-structs-interfaces skill takes precedence. Go Structs & Interfaces Interface Design Principles Keep Interfaces Small "The bigger the interface, the weaker the abstraction." — Go Proverbs Interfaces SHOULD have 1-3 methods. Small...
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| 2129 | dart-migrate-to-checks-package | dart-lang/skills |
Migrating Dart Tests to Package Checks Contents Dependency Management Syntax Migration Guidelines Utilizing Dart MCP Tools Migration Workflow Examples Dependency Management Manage dependencies using the Dart Tooling MCP Server pub tool or standard CLI commands. Add package:checks as a dev_dependency using dart pub add dev:checks . Remove package:matcher if it is explicitly listed in the pubspec.yaml (note: it is often transitively included by package:test , which is fine). Import package:checks/...
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| 2130 | dart-build-cli-app | dart-lang/skills |
Building Dart CLI Applications Contents Project Setup & Architecture Argument Parsing & Command Routing Execution & Error Handling Testing CLI Applications Compilation & Distribution Workflows Examples Project Setup & Architecture Initialize new CLI projects using the official Dart template to ensure standard directory structures. Run dart create -t cli <project_name> to scaffold a console application with basic argument parsing. Place executable entry points (files containing main() ) exclusive...
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| 2131 | sound-effects | elevenlabs/skills |
ElevenLabs Sound Effects Generate sound effects from text descriptions — supports looping, custom duration, and prompt adherence control. Setup: See Installation Guide . For JavaScript, use @elevenlabs/* packages only. Quick Start Python from elevenlabs . client import ElevenLabs client = ElevenLabs ( ) audio = client . text_to_sound_effects . convert ( text = "Thunder rumbling in the distance with light rain" , ) with open ( "thunder.mp3" , "wb" ) as f : for chunk in audio : f . write ( chunk )...
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| 2132 | dogfood | nousresearch/hermes-agent |
Dogfood Systematically explore a web application, find issues, and produce a report with full reproduction evidence for every finding. Setup Only the Target URL is required. Everything else has sensible defaults -- use them unless the user explicitly provides an override. Parameter Default Example override Target URL (required) vercel.com , http://localhost:3000 Session name Slugified domain (e.g., vercel.com -> vercel-com ) --session my-session Output directory ./dogfood-output/ Output director...
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| 2133 | macos-design-guidelines | ehmo/platform-design-skills |
macOS Human Interface Guidelines Mac apps serve power users who expect deep keyboard control, persistent menu bars, resizable multi-window layouts, and tight system integration. These guidelines codify Apple's HIG into actionable rules with SwiftUI and AppKit examples. 1. Menu Bar (CRITICAL) Every Mac app must have a menu bar. It is the primary discovery mechanism for commands. Users who cannot find a feature will look in the menu bar before anywhere else. Rule 1.1 — Provide Standard Menus Every...
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| 2134 | youtube-transcript | intellectronica/agent-skills |
YouTube Transcript Extract transcripts from YouTube videos using the youtube-transcript-api. Usage Run the script with a YouTube URL or video ID: uv run scripts/get_transcript.py "VIDEO_URL_OR_ID" With timestamps: uv run scripts/get_transcript.py "VIDEO_URL_OR_ID" --timestamps Defaults Without timestamps (default): Plain text, one line per caption segment With timestamps: [MM:SS] text format (or [HH:MM:SS] for longer videos) Supported URL Formats https://www.youtube.com/watch?v=VIDEO_ID ...
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| 2135 | dart-flutter-patterns | affaan-m/everything-claude-code |
Dart/Flutter Patterns When to Use Use this skill when: Starting a new Flutter feature and need idiomatic patterns for state management, navigation, or data access Reviewing or writing Dart code and need guidance on null safety, sealed types, or async composition Setting up a new Flutter project and choosing between BLoC, Riverpod, or Provider Implementing secure HTTP clients, WebView integration, or local storage Writing tests for Flutter widgets, Cubits, or Riverpod providers Wiring up GoRouter...
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| 2136 | ctf-writeup | ljagiello/ctf-skills |
CTF Write-up Generator Generate a standardized submission-style CTF writeup for a solved challenge. Default behavior: During an active competition, optimize for speed, clarity, and reproducibility Keep writeups short enough that a teammate or organizer can validate the solve quickly Always produce a submission -style writeup Prefer one complete solve script from challenge data to final flag Workflow Step 1: Gather Information Collect the following from the current session, challenge files, and u...
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| 2137 | ljg-paper-flow | lijigang/ljg-skills |
ljg-paper-flow: 论文流 一条命令完成:读论文 → 生成解读 → 铸成卡片。支持多篇并行。 模式 强制 NATIVE 模式。 本 workflow 是纯 skill 管道(ljg-paper → ljg-card),不需要 Algorithm 的七步流程。直接按下方执行步骤调用 skill,不走 OBSERVE/THINK/PLAN/BUILD/EXECUTE/VERIFY/LEARN。 参数 参数 说明 无参数 对话中已提供的论文链接/文件 -l 卡片模具改用长图模式(默认 -c 漫画) -i 卡片模具改用信息图模式 执行 1. 收集论文列表 从用户消息中提取所有论文来源(arxiv URL、PDF 路径、论文名称等)。 2. 并行处理每篇论文 对每篇论文,启动一个 Agent subagent,每个 subagent 按顺序执行两步: 步骤 A — 读论文(ljg-paper): 调用 Skill tool 执行 ljg-paper ,传入该论文的来源。等待完成,获得生成的 org 文件路径。 步骤 B — 铸卡片(ljg-card): 读取步骤 A 生成的 org ...
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| 2138 | smart-explore | thedotmack/claude-mem |
Smart Explore Structural code exploration using AST parsing. This skill overrides your default exploration behavior. While this skill is active, use smart_search/smart_outline/smart_unfold as your primary tools instead of Read, Grep, and Glob. Core principle: Index first, fetch on demand. Give yourself a map of the code before loading implementation details. The question before every file read should be: "do I need to see all of this, or can I get a structural overview first?" The answer is almo...
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| 2139 | golang-modernize | samber/cc-skills-golang |
Persona: You are a Go modernization engineer. You keep codebases current with the latest Go idioms and standard library improvements — you prioritize safety and correctness fixes first, then readability, then gradual improvements. Modes: Inline mode (developer is actively coding): suggest only modernizations relevant to the current file or feature; mention other opportunities you noticed but do not touch unrelated files. Full-scan mode (explicit /golang-modernize invocation or CI): use up to 5 p...
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| 2140 | html-slides | claude-office-skills/skills |
HTML Slides Skill Overview This skill enables creation of stunning HTML-based presentations using reveal.js - the web's most popular presentation framework. Create interactive, responsive slides with animations, code highlighting, speaker notes, and more. How to Use Describe the presentation you want to create Specify theme, transitions, and features needed I'll generate a reveal.js presentation Example prompts: "Create an interactive presentation about our product" "Build a code walkthrough pre...
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| 2141 | ljg-skill-map | lijigang/ljg-skills |
ljg-skill-map: 技能地图 扫描 ~/.claude/skills/ 下所有已安装技能,生成一目了然的可视化地图。 执行 1. 扫描 运行 scripts/scan.sh ,获取所有技能的 JSON 数据(name, version, invocable, desc)。 2. 分类 根据技能名称和描述,将技能自动归入以下类别: 类别 图标 含义 典型成员 认知原子 ◆ 内容处理的原子操作 ljg-plain, ljg-word, ljg-writes, ljg-paper 输出铸造 ▲ 将内容转化为可交付物 ljg-card 联网触达 ● 与外部世界交互 agent-reach 系统运维 ■ Agent 自身的维护和管理 datetime-check, memory-review, save-conversation, skill-creator, ljg-skill-map 环境部署 ★ 一次性安装和配置 Her-init 归类依据名称前缀和描述关键词判断。遇到新技能无法归类时,放入「未分类」。 3. 渲染 用 ASCII 方框图呈现,格式如下: ╔═══════════...
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| 2142 | ljg-word | lijigang/ljg-skills |
Usage Instructions 目标不是翻译,而是让用户掌握这个词的深层含义和用法。 针对输入的 word (转换为小写,首字母大写),进行以下分析,直接在对话中用 Markdown 输出: 输出结构 1. 标题行 {Word} /{音标}/ {中文翻译} 2. 核心语义 原始画面 : 用一句话描述该词源头最物理的画面(例如 Incubate: 母鸡趴在蛋上)。 核心意象 : 提炼公式(例如:温暖 + 时间 + 保护 = 孕育)。 解释 : 用充满洞见的语言阐述其深层含义与现代用法。分段清晰, 加粗 关键词。要有穿透力,展现词源、多领域含义之间的内在联系。 3. 一语道破 一句中英双语的金句,必须具有哲学高度,总结该词的灵魂。用引用格式: > "English sentence. 中文金句。"
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| 2143 | lead-intelligence | affaan-m/everything-claude-code |
Lead Intelligence Agent-powered lead intelligence pipeline that finds, scores, and reaches high-value contacts through social graph analysis and warm path discovery. When to Activate User wants to find leads or prospects in a specific industry Building an outreach list for partnerships, sales, or fundraising Researching who to reach out to and the best path to reach them User says "find leads", "outreach list", "who should I reach out to", "warm intros" Needs to score or rank a list of contacts ...
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| 2144 | golang-observability | samber/cc-skills-golang |
Persona: You are a Go observability engineer. You treat every unobserved production system as a liability — instrument proactively, correlate signals to diagnose, and never consider a feature done until it is observable. Modes: Coding / instrumentation (default): Add observability to new or existing code — declare metrics, add spans, set up structured logging, wire pprof toggles. Follow the sequential instrumentation guide. Review mode — reviewing a PR's instrumentation changes. Check that new c...
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| 2145 | web-research | langchain-ai/deepagents |
Web Research Skill This skill provides a structured approach to conducting comprehensive web research using the task tool to spawn research subagents. It emphasizes planning, efficient delegation, and systematic synthesis of findings. When to Use This Skill Use this skill when you need to: Research complex topics requiring multiple information sources Gather and synthesize current information from the web Conduct comparative analysis across multiple subjects Produce well-sourced research rep...
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| 2146 | make-plan | thedotmack/claude-mem |
Make Plan You are an ORCHESTRATOR. Create an LLM-friendly plan in phases that can be executed consecutively in new chat contexts. Delegation Model Use subagents for fact gathering and extraction (docs, examples, signatures, grep results). Keep synthesis and plan authoring with the orchestrator (phase boundaries, task framing, final wording). If a subagent report is incomplete or lacks evidence, re-check with targeted reads/greps before finalizing. Subagent Reporting Contract (MANDATORY) Each sub...
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| 2147 | agent-email-inbox | resend/resend-skills |
AI Agent Email Inbox Overview This skill covers setting up a secure email inbox that allows your application or AI agent to receive and respond to emails, with content safety measures in place. Core principle: An AI agent's inbox receives untrusted input. Security configuration is important to handle this safely. Why Webhook-Based Receiving? Resend uses webhooks for inbound email, meaning your agent is notified instantly when an email arrives. This is valuable for agents because: Real-time respo...
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| 2148 | gan-style-harness | affaan-m/everything-claude-code |
GAN-Style Harness Skill Inspired by Anthropic's Harness Design for Long-Running Application Development (March 24, 2026) A multi-agent harness that separates generation from evaluation , creating an adversarial feedback loop that drives quality far beyond what a single agent can achieve. Core Insight When asked to evaluate their own work, agents are pathological optimists — they praise mediocre output and talk themselves out of legitimate issues. But engineering a separate evaluator to be ruthle...
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| 2149 | golang-lint | samber/cc-skills-golang |
Persona: You are a Go code quality engineer. You treat linting as a first-class part of the development workflow — not a post-hoc cleanup step. Modes: Setup mode — configuring .golangci.yml , choosing linters, enabling CI: follow the configuration and workflow sections sequentially. Coding mode — writing new Go code: launch a background agent running golangci-lint run --fix on the modified files only while the main agent continues implementing the feature; surface results when it completes. Inte...
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| 2150 | golang-dependency-injection | samber/cc-skills-golang |
Persona: You are a Go software architect. You guide teams toward testable, loosely coupled designs — you choose the simplest DI approach that solves the problem, and you never over-engineer. Modes: Design mode (new project, new service, or adding a service to an existing DI setup): assess the existing dependency graph and lifecycle needs; recommend manual injection or a library from the decision table; then generate the wiring code. Refactor mode (existing coupled code): use up to 3 parallel sub...
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