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This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows,

Generate a beautiful HTML landing page from your package.json. Use when you need a quick marketing page for your project.

Comprehensive guide for creating effective landing pages using Next.js or React. This skill should be used when users request to create landing pages, marketing pages, or product pages that require the 11 essential elements for high-converting landing pages. Specifically

Create distinctive, high-converting landing pages that combine proven conversion elements with exceptional design quality. Build beautiful, memorable landing pages using Next.js 14+ and ShadCN UI that avoid generic AI aesthetics while following the 11 essential elements

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

Configure LangChain CI/CD integration with GitHub Actions and testing.\nUse when setting up automated testing, configuring CI pipelines,\nor integrating LangChain tests into your build process.\nTrigger with phrases like \

Diagnose and fix common LangChain errors and exceptions.\nUse when encountering LangChain errors, debugging failures,\nor troubleshooting integration issues.\nTrigger with phrases like \

Optimize LangChain API costs and token usage.\nUse when reducing LLM API expenses, implementing cost controls,\nor optimizing token consumption in production.\nTrigger with phrases like \

Deploy LangChain integrations to production environments.\nUse when deploying to cloud platforms, configuring containers,\nor setting up production infrastructure for LangChain apps.\nTrigger with phrases like \

Incident response procedures for LangChain production issues.\nUse when responding to production incidents, diagnosing outages,\nor implementing emergency procedures for LLM applications.\nTrigger with phrases like \

Install and configure LangChain SDK/CLI authentication.\nUse when setting up a new LangChain integration, configuring API keys,\nor initializing LangChain in your project.\nTrigger with phrases like \

Configure LangChain local development workflow with hot reload and testing.\nUse when setting up development environment, configuring test fixtures,\nor establishing a rapid iteration workflow for LangChain apps.\nTrigger with phrases like \

Complex migration strategies for LangChain applications.\nUse when migrating from legacy LLM frameworks, refactoring large codebases,\nor implementing phased migration approaches.\nTrigger with phrases like \

Configure LangChain multi-environment setup for dev/staging/prod.\nUse when managing multiple environments, configuring environment-specific settings,\nor implementing environment promotion workflows.\nTrigger with phrases like \

Optimize LangChain application performance and latency.\nUse when reducing response times, optimizing throughput,\nor improving the efficiency of LangChain pipelines.\nTrigger with phrases like \

Execute LangChain production deployment checklist.\nUse when preparing for production launch, validating deployment readiness,\nor auditing existing production LangChain applications.\nTrigger with phrases like \

Apply LangChain security best practices for production.\nUse when securing API keys, preventing prompt injection,\nor implementing safe LLM interactions.\nTrigger with phrases like \

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when:

Configure Langfuse CI/CD integration with GitHub Actions and automated testing.\nUse when setting up automated testing, configuring CI pipelines,\nor integrating Langfuse tests into your build process.\nTrigger with phrases like \

Execute Langfuse secondary workflow: Evaluation and scoring.\nUse when implementing LLM evaluation, adding user feedback,\nor setting up automated quality scoring for AI outputs.\nTrigger with phrases like \

Monitor and optimize LLM costs using Langfuse analytics and dashboards.\nUse when tracking LLM spending, identifying cost anomalies,\nor implementing cost controls for AI applications.\nTrigger with phrases like \

Collect Langfuse debug evidence for support tickets and troubleshooting.\nUse when encountering persistent issues, preparing support tickets,\nor collecting diagnostic information for Langfuse problems.\nTrigger with phrases like \

Deploy Langfuse with your application across different platforms.\nUse when deploying Langfuse to Vercel, AWS, GCP, or Docker,\nor integrating Langfuse into your deployment pipeline.\nTrigger with phrases like \

Create a minimal working Langfuse trace example.\nUse when starting a new Langfuse integration, testing your setup,\nor learning basic Langfuse tracing patterns.\nTrigger with phrases like \

Install and configure Langfuse SDK authentication for LLM observability.\nUse when setting up a new Langfuse integration, configuring API keys,\nor initializing Langfuse tracing in your project.\nTrigger with phrases like \

Set up Langfuse local development workflow with hot reload and debugging.\nUse when developing LLM applications locally, debugging traces,\nor setting up a fast iteration loop with Langfuse.\nTrigger with phrases like \

Langfuse production readiness checklist and verification.\nUse when preparing to deploy Langfuse to production,\nvalidating production configuration, or auditing existing setup.\nTrigger with phrases like \

Implement Langfuse rate limiting, batching, and backoff patterns.\nUse when handling rate limit errors, optimizing trace ingestion,\nor managing high-volume LLM observability workloads.\nTrigger with phrases like \

Production-grade Langfuse architecture patterns and best practices.\nUse when designing LLM observability infrastructure, planning Langfuse deployment,\nor implementing enterprise-grade tracing architecture.\nTrigger with phrases like \

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production

Use this skill for requests related to LangGraph in order to fetch relevant documentation to provide accurate, up-to-date guidance.

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

Core architectural standards for scalable Laravel applications.

Generate PDFs from Blade views or HTML using spatie/laravel-pdf. Covers creating, formatting, saving, downloading, and testing PDFs with the Browsershot, Cloudflare, or DOMPDF driver.

Use when building Laravel 10+ applications requiring Eloquent ORM, API resources, or queue systems. Invoke for Laravel models, Livewire components, Sanctum authentication, Horizon queues.

帮助用户创建飞书文档

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

Access Last.fm listening history, music stats, and discovery. Query recent tracks, top artists/albums/tracks, loved tracks, similar artists, and global charts.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific

Build, install, and launch the Zhihu++ Android app on a connected device using ADB. Includes comprehensive troubleshooting for common issues like missing devices, installation failures, signature mismatches, and app crashes. Use when deploying debug builds to physical devices or

When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' or 'product update.' This skill covers

Analyze document structure and layout using surya - detect text blocks, tables, and reading order

Identify components that should be lazy loaded. Use when optimizing bundle size.

LazyLLM framework for building multi-agent AI applications. Use when task mentioned LazyLLM or AI program for: (1) Flow orchestration - linear, branching, parallel, loop workflows for complex data pipelines, (2) Model fine-tuning and acceleration - finetuning LLMs with

Guide for Lightdash's CASL-based authorization system. Use when working with scopes, custom roles, abilities, permissions, ForbiddenError, authorization, or access control. Helps with adding new scopes, debugging permission issues, understanding the permission flow, and creating