sequential-thinking 是做什麼的？
在處理需要系統性逐步推理的複雜問題時使用，具備修改思路、分支至替代方法或動態調整範圍的能力。適用於多階段分析、設計規劃、問題分解，或初始範圍不明確的任務。
在處理需要系統性逐步推理的複雜問題時使用，具備修改思路、分支至替代方法或動態調整範圍的能力。適用於多階段分析、設計規劃、問題分解，或初始範圍不明確的任務。
此技能旨在提供系統性的逐步推理能力，幫助用戶拆解複雜問題並進行多階段分析。它支持動態調整思考範圍、修改已有思路，並可分支至替代解決方案，特別適合範圍不明確或需要反覆迭代的任務。該技能通常用於設計規劃、問題分解和高階邏輯推理場景，能顯著提升AI代理在結構化思考任務中的表現。它與主流的開發工具和AI代理平台兼容，通過引導用戶以有序步驟處理問題，減少認知負荷並提高輸出品質。
npx skills add https://github.com/mrgoonie/claudekit-skills/tree/main/skills/sequential-thinkingInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
在處理需要系統性逐步推理的複雜問題時使用，具備修改思路、分支至替代方法或動態調整範圍的能力。適用於多階段分析、設計規劃、問題分解，或初始範圍不明確的任務。
This repo contains 3 individual skills — each has its own dedicated page.
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing imag
Build 3D web apps with Three.js (WebGL/WebGPU). Use for 3D scenes, animations, custom shaders, PBR materials, VR/XR experiences, games, data visualizations, product configurators.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.