sequential-thinking 是做什么的？
用于需要系统性逐步推理的复杂问题，支持修正思路、分支探索替代方案或动态调整范围。适用于多阶段分析、设计规划、问题分解或初始范围不明确的任务。
用于需要系统性逐步推理的复杂问题，支持修正思路、分支探索替代方案或动态调整范围。适用于多阶段分析、设计规划、问题分解或初始范围不明确的任务。
该技能是一个针对AI代理（如Claude Code、Cursor、Codex等）的“顺序思维”技能，旨在帮助处理需要逐步推理的复杂问题。它允许代理系统性地分解问题，逐步推进分析，同时具备灵活调整的能力：可以随时修正之前的思路、分支到替代方案，或根据进展动态调整任务范围。该技能特别适用于多阶段分析、设计规划、问题分解，以及那些初始范围不明确或需要迭代优化的任务场景。通过提供结构化的思维框架，它提升了AI代理处理复杂任务的效率和准确性，并支持在推理过程中保存和回溯中间状态。该技能适用于所有主要AI代理平台，且无需额外依赖即可使用。
npx skills add https://github.com/mrgoonie/claudekit-skills/tree/main/skills/sequential-thinkingInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
用于需要系统性逐步推理的复杂问题，支持修正思路、分支探索替代方案或动态调整范围。适用于多阶段分析、设计规划、问题分解或初始范围不明确的任务。
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.