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perplexity-search
by AIsa-team
"Perplexity Sonar search and answer generation through AIsa. Use when the task is specifically to call Perplexity Sonar, Sonar Pro, Sonar Reasoning Pro, or Sonar Deep Research for citation-backed web answers, analytical reasoning, or long-form research reports."
prediction-market-arbitrage
by AIsa-team
"Find and analyze arbitrage opportunities across prediction markets like Polymarket and Kalshi."
ljg-paper-flow
by lijigang
"Paper workflow: read papers + cast cards in one go. Takes one or more arxiv links, paper URLs, PDFs, or paper names. For each paper, runs ljg-paper (generates org analysis) then ljg-card -v (generates visual sketchnote PNG). Use when user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers wanting both analysis and cards."
benchclaw - openclaw-benchmark
by BenchClaw
BenchClaw - OpenClaw Agent benchmark scoring tool. Benchmark 跑分 评测 打分. BenchClaw是专业级 OpenClaw Agent 性能评测框架。它专注于对 AI Agent 进行多维度、 自动化的量化评估与能力基准测试，集成了任务分发、精准评分、可视化报表生成及热更新功能。 当需要量化 Agent 的推理规划、响应速度、Token 成本及安全性时使用。 用户意图/指令：跑分、跑个分、运行基准测试、评估 Agent 表现、生成评测报告、分析 Token 消耗。 技术关键词：跑分、跑个分、Agent 评测、基准测试、自动化打分、量化评估、性能报告、Token 成本、 TPS、OpenClaw。 BenchClaw is the "AnTuTu" for OpenClaw Agents—a professional-grade automated benchmarking framework. It provides multi-dimensional evaluation (Capability, Config, Security, Hardware, Permission) through automated task execution, precision scoring, and detailed report generation. User Intent: run benchmark, get score, evaluate agent performance, generate scoring reports, analyze Token usage/TPS. Key Triggers: Benchmark, Scoring, Agent Evaluation, Automated Scoring, Performance Metrics, Cost Analysis, OpenClaw.
ljg-card
by lijigang
"Content caster (铸). Transforms content into PNG visuals. Seven molds: -l (default) long reading card, -i infograph, -m multi-card reading cards (1080x1440), -v visual sketchnote, -c comic (manga-style B&W), -w whiteboard (marker-style board layout), -b big-fonts attachment card (1080x1440, weathered 碑刻 style for 小红书). Output to ~/Downloads/. Use when user says '铸', 'cast', '做成图', '做成卡片', '做成信息图', '做成海报', '视觉笔记', 'sketchnote', '漫画', 'comic', 'manga', '白板', 'whiteboard', '大字', '附件图', 'big fonts', '小红书卡片'. Replaces ljg-cards and ljg-infograph."
investment-analysis
by xgwu
通用投资分析框架 V3.1 - 支持A股/港股/美股的深度价值投资分析，含多层数据降级、数据验证、大师三视角
thetanuts
by goheesheng
Trade crypto options on Thetanuts Finance - orderbook fills, RFQ lifecycle, multi-strike structures, real-time WebSocket, wallet management, early settlement, referrer fees
wechat-article-spider
by wanhuhou1983
微信公众号文章抓取并转换为 Markdown + 本地图片。基于 Playwright Firefox 浏览器自动化 + markdownify 高质量转换。
gpt-image-2-generation
by yun520-1
通用的对话生图技能。先发现已配置的 OpenAI 兼容 API，再验证是否支持 gpt-image-2，随后生成图片并保存为本地文件。适合所有 AI 使用，不绑定 HeartFlow。
analytics-tracking-automation
by jtrackingai
Use when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.
ifq-design-skills
by peixl
"Use this skill whenever the user asks for an HTML-first visual design deliverable or design judgment: interactive prototype, slide deck, motion demo, infographic, dashboard, landing page, whitepaper, changelog, business card, social cover, brand system, design critique, multi-variant exploration, or export to MP4, GIF, PPTX, PDF, or SVG. It is optimized to make AI agents do the routing, template selection, verification, and export prep so humans spend less time prompt-engineering. Do not use for production web apps, SEO sites, backend systems, or pure copy edits."
gpt-image-2
by ConardLi
面向 GPT Image 2 的图像生成 / 编辑技能。可在 3 种环境下使用：(A) Garden 本地模式，通过 OpenAI 兼容接口直接出图并落盘；(B) Host-Native 模式，把本 Skill 当作提示词工程指引，把渲染好的 prompt 交给宿主 Agent 自带的图像工具出图；(C) Advisor 模式，宿主无任何图像工具时退化为高质量 prompt 顾问。涵盖 18 大类、80+ 个结构化模板，覆盖海报 / UI / 产品 / 信息图 / 学术图 / 技术架构图 / 漫画 / 头像 / 流程板 / 电影分镜 / IP 周边 / 编辑工作流等场景。
javascript-pro
by Jeffallan
Writes, debugs, and refactors JavaScript code using modern ES2023+ features, async/await patterns, ESM module systems, and Node.js APIs. Use when building vanilla JavaScript applications, implementing Promise-based async flows, optimising browser or Node.js performance, working with Web Workers or Fetch API, or reviewing .js/.mjs/.cjs files for correctness and best practices.
laravel-specialist
by Jeffallan
Build and configure Laravel 10+ applications, including creating Eloquent models and relationships, implementing Sanctum authentication, configuring Horizon queues, designing RESTful APIs with API resources, and building reactive interfaces with Livewire. Use when creating Laravel models, setting up queue workers, implementing Sanctum auth flows, building Livewire components, optimising Eloquent queries, or writing Pest/PHPUnit tests for Laravel features.
flutter-expert
by Jeffallan
Use when building cross-platform applications with Flutter 3+ and Dart. Invoke for widget development, Riverpod/Bloc state management, GoRouter navigation, platform-specific implementations, performance optimization.
kubernetes-specialist
by Jeffallan
Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.
cloud-architect
by Jeffallan
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.
dotnet-core-expert
by Jeffallan
Use when building .NET 8 applications with minimal APIs, clean architecture, or cloud-native microservices. Invoke for Entity Framework Core, CQRS with MediatR, JWT authentication, AOT compilation.
fastapi-expert
by Jeffallan
"Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python."
php-pro
by Jeffallan
Use when building PHP applications with modern PHP 8.3+ features, Laravel, or Symfony frameworks. Invokes strict typing, PHPStan level 9, async patterns with Swoole, and PSR standards. Creates controllers, configures middleware, generates migrations, writes PHPUnit/Pest tests, defines typed DTOs and value objects, sets up dependency injection, and scaffolds REST/GraphQL APIs. Use when working with Eloquent, Doctrine, Composer, Psalm, ReactPHP, or any PHP API development.
python-pro
by Jeffallan
Use when building Python 3.11+ applications requiring type safety, async programming, or robust error handling. Generates type-annotated Python code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, and validates code with black and ruff. Invoke for type hints, async/await patterns, dataclasses, dependency injection, logging configuration, and structured error handling.
mcp-developer
by Jeffallan
Use when building, debugging, or extending MCP servers or clients that connect AI systems with external tools and data sources. Invoke to implement tool handlers, configure resource providers, set up stdio/HTTP/SSE transport layers, validate schemas with Zod or Pydantic, debug protocol compliance issues, or scaffold complete MCP server/client projects using TypeScript or Python SDKs.
pandas-pro
by Jeffallan
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.
rag-architect
by Jeffallan
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality. Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, context augmentation, similarity search, or embedding-based indexing.