project-development
Methodology for identifying LLM-suited tasks, designing pipelines, and iterating with agent-assisted development.
浏览 5dlabs 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
104收录技能的仓库 Stars 合计
140仓库 Forks
15平均每个技能的仓库 Stars
1同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Methodology for identifying LLM-suited tasks, designing pipelines, and iterating with agent-assisted development.
Rust backend patterns including Axum, Tokio, error handling with anyhow/thiserror, and tracing.
Extend effective context capacity through compression, masking, caching, and partitioning techniques.
Fetch LLM-optimized documentation for Supabase, the open-source Firebase alternative.
Test-driven development discipline - RED-GREEN-REFACTOR cycle with strict enforcement. Use when implementing any feature or bugfix, before writing implementation code.
Decision framework for choosing between shadcn (SSR/SEO) and TanStack (real-time/client-first) frontend stacks
Official Expo UI guidelines - build beautiful apps with Expo Router, NativeTabs, SF Symbols, animations, and Apple HIG patterns
Linear Agent API expertise - sessions, activities, signals, and best practices. Use when working with Linear agent integration, verifying dialogue population, or implementing two-way communication.
Patterns for testing local web applications using Playwright. Use when verifying frontend functionality, debugging UI behavior, capturing screenshots, or testing dynamic web apps. Provides decision tree for cho...
React and Next.js performance optimization guidelines. Use when writing, reviewing, or refactoring React/Next.js code. Applies to Blaze (web), Spark (desktop), and Tap (mobile) agents.
Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references
Semantic code research across GitHub repositories for finding implementations, patterns, and conducting PR/security reviews.
Guide for creating MCP (Model Context Protocol) servers that enable LLMs to interact with external services. Use when building MCP servers, integrating external APIs, implementing tool servers, or creating agen...
Recognize and mitigate context failures including lost-in-middle, context poisoning, distraction, confusion, and clash.
Foundational understanding of context engineering for AI agent systems - context windows, attention mechanics, progressive disclosure, and context budgeting
Fetch LLM-optimized documentation for tRPC, the end-to-end typesafe API framework.
Design effective tools for AI agents - tool descriptions, consolidation principles, architectural reduction, MCP naming conventions, and error handling
Create distinctive, production-grade frontend interfaces with high design quality. Use when building UI components, pages, or applications to avoid generic AI aesthetics.
Fetch Expo documentation via llms.txt for up-to-date React Native development references
Better Auth integration for Electron desktop apps with secure IPC, context isolation, and encrypted session storage
CTO Platform lifecycle expertise - Play workflow orchestration, intake processing, MCP tools, and agent sequencing. Use when managing the full development lifecycle from PRD to deployed code.
Create distinctive, production-grade frontend interfaces that avoid generic AI aesthetics. Use when building web UIs, React components, landing pages, dashboards, or styling any web interface. Provides design t...
Pull request review patterns including focus areas, feedback guidelines, and approval criteria.
CTO observability stack expertise - Prometheus metrics, Loki logs, Grafana dashboards. Use when querying logs, metrics, or debugging via telemetry.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。