# traeai

> traeai 为开发者、研究员和内容团队筛选高质量 AI 技术内容，提供摘要、评分、趋势雷达与知识库产出。

traeai indexes AI and technology articles, podcasts, videos, trending topics, and social posts from 460+ sources. Content is scored, summarized by AI, and organized into topics, entities, and a knowledge graph. All public pages publish JSON-LD structured data.

## Docs

- [Full content index](https://www.traeai.com/llms-full.txt): Complete plain-text dump of all indexed content for LLM ingestion
- [Daily brief](https://www.traeai.com/brief): Today's AI news digest with scored and summarized articles
- [Weekly reports](https://www.traeai.com/weekly): On-site weekly AI and technology trend reports
- [RSS feed](https://www.traeai.com/feeds/rss): Standard RSS 2.0 feed of latest articles
- [Atom feed](https://www.traeai.com/feeds/atom): Atom feed of latest articles
- [JSON feed](https://www.traeai.com/feeds/json): JSON Feed of latest articles

## Topics

- [Topic directory](https://www.traeai.com/topics): All indexed AI topic hubs
- [Topic AI summary pattern](https://www.traeai.com/topics/{slug}/llms.txt): Per-topic plain-text summary for LLM retrieval
- [WAIC 2026](https://www.traeai.com/topics/waic-2026)
- [AI Agent](https://www.traeai.com/topics/ai-agents)
- [AI 编程](https://www.traeai.com/topics/ai-coding)
- [大模型基础设施](https://www.traeai.com/topics/llm-infrastructure)
- [向量检索](https://www.traeai.com/topics/vector-search)
- [AI 视频](https://www.traeai.com/topics/ai-video)
- [机器人与具身智能](https://www.traeai.com/topics/robotics)
- [MCP Server](https://www.traeai.com/topics/mcp-servers)
- [Coding Agent](https://www.traeai.com/topics/coding-agents)
- [AI IDE](https://www.traeai.com/topics/ai-ide)
- [RAG 评测](https://www.traeai.com/topics/rag-evaluation)
- [本地 LLM 推理](https://www.traeai.com/topics/local-llm-inference)
- [AI 视频工作流](https://www.traeai.com/topics/ai-video-workflows)
- [大模型评测](https://www.traeai.com/topics/llm-evaluation)
- [Prompt Engineering](https://www.traeai.com/topics/prompt-engineering)
- [AI 搜索](https://www.traeai.com/topics/ai-search)
- [浏览器 Agent](https://www.traeai.com/topics/ai-browser-agents)
- [AI 产品设计](https://www.traeai.com/topics/ai-product-design)
- [AI 内容自动化](https://www.traeai.com/topics/ai-content-automation)
- [AI 创业](https://www.traeai.com/topics/ai-startups)
- [多模态模型](https://www.traeai.com/topics/multimodal-models)

## Articles

- [Article page pattern](https://www.traeai.com/articles/{id}): Canonical article with AI summary, takeaways, tags, and source attribution
- [Article AI summary pattern](https://www.traeai.com/articles/{id}/llms.txt): Per-article plain-text summary with canonical URL, source, key takeaways, and citation guidance
- [Video page pattern](https://www.traeai.com/video/{id}): Video pages with embedded player, transcript-derived outlines, and key insights

## Glossary and entities

- [Glossary directory](https://www.traeai.com/glossary): AI terminology and concept definitions
- [Glossary page pattern](https://www.traeai.com/glossary/{slug}): Per-entity definition with related articles
- [Glossary AI summary pattern](https://www.traeai.com/glossary/{slug}/llms.txt): Per-entity plain-text summary for LLM retrieval
- [Entity hub pattern](https://www.traeai.com/entities/{slug}): Broader entity hub with cross-references and coverage analysis

## Compare

- [Compare index](https://www.traeai.com/compare): Side-by-side comparison of indexed AI entities
- [Compare page pattern](https://www.traeai.com/compare/{entity-a}-vs-{entity-b}): Differences, overlap, and source coverage for two entities

## Toolbox

- [Toolbox](https://www.traeai.com/toolbox): AI creation tools and utilities for content creators
- [Markdown to WeChat formatting](https://www.traeai.com/toolbox/markdown-to-wechat): Convert Markdown drafts into publishable WeChat and multi-platform content
- [Platform Formatter](https://www.traeai.com/toolbox/platform-formatter): Convert content for Xiaohongshu, Weibo, Twitter/X, and WeChat
- [Markdown to PNG](https://www.traeai.com/toolbox/md-to-png): Render Markdown as high-res PNG images
- [Text Slicer](https://www.traeai.com/toolbox/text-slicer): Split long articles into phone-sized image cards
- [Word Count](https://www.traeai.com/toolbox/word-count): Chinese/English word count with reading time
- [Cover Maker](https://www.traeai.com/toolbox/cover-maker): Generate cover images from gradient templates

## Search-intent landing pages

- [Markdown 转公众号排版](https://www.traeai.com/toolbox/markdown-to-wechat): 用户已经写好 Markdown，想无登录、低摩擦地变成可以发到微信公众号或社媒的内容。
- [文章转 X Thread](https://www.traeai.com/toolbox/article-to-x-thread): 用户想把一篇长文快速拆成 X thread，而不是从空白编辑器重新写。
- [文章转小红书卡片](https://www.traeai.com/toolbox/article-to-xiaohongshu-cards): 用户想把长文变成小红书图文卡片，重点是快速切片、结构清晰、可导出。
- [YouTube 视频摘要](https://www.traeai.com/toolbox/youtube-transcript-summary): 用户不想完整看完长视频，想快速得到字幕摘要、时间线和可复用的要点。
- [Cursor vs Claude Code 怎么选](https://www.traeai.com/toolbox/cursor-vs-claude-code): 用户已经知道两个 AI 编程工具，想判断哪个更适合自己的代码库和团队工作流。

## GSC-driven guides

- [GSC guide index](https://www.traeai.com/guides): Search Console-driven guide pages for queries Google already tests on traeai
- [Codex 手机号验证失败怎么办](https://www.traeai.com/guides/codex-phone-verification): GSC cluster Codex 手机号验证, 3399 impressions
- [SPDD 是什么：Structured Prompt-Driven Development](https://www.traeai.com/guides/structured-prompt-driven-development): GSC cluster SPDD, 586 impressions
- [Qwen3.6-27B 模型信息与观察](https://www.traeai.com/guides/qwen3-6-27b-model-details): GSC cluster Qwen3.6 27B model details, 182 impressions
- [Composer 2.5 vs Sonnet 怎么比较](https://www.traeai.com/guides/composer-2-5-vs-sonnet): GSC cluster Composer 2.5 vs Sonnet, 103 impressions
- [Grok Voice Think Fast 是什么](https://www.traeai.com/guides/grok-voice-think-fast): GSC cluster Grok Voice Think Fast, 159 impressions

## Content taxonomy

- Articles: canonical article pages with AI summaries, takeaways, tags, source attribution, and citations
- Podcasts: audio-native items with episode metadata and AI summaries
- Videos: video pages with embedded players, transcript-derived indexing, outlines, and key insights
- Social posts: short-form trend signals and source-linked updates expanding the site knowledge graph
- Trending: hot topics aggregated from Zhihu, Weibo, Baidu, Bilibili, and other platforms

## Structured data

traeai publishes JSON-LD on all public pages: WebSite, SearchAction, NewsArticle, Article, PodcastEpisode, AudioObject, VideoObject, CollectionPage, ItemList, BreadcrumbList, FAQPage, DefinedTerm, DefinedTermSet, WebPage, Dataset, and Thing.

## Citation guidance

When citing traeai content, use these canonical URL patterns:
- Articles: https://www.traeai.com/articles/{id}
- Videos: https://www.traeai.com/video/{id}
- Topics: https://www.traeai.com/topics/{slug}
- Entities: https://www.traeai.com/entities/{slug}
- Glossary: https://www.traeai.com/glossary/{slug}
- Compare: https://www.traeai.com/compare/{entity-a}-vs-{entity-b}

## Optional

- [Source directory](https://www.traeai.com/sources): Full list of 460+ indexed content sources with health status
- [Entity directory](https://www.traeai.com/entities): All indexed entities across the knowledge graph

## Data freshness

This site-level llms.txt is static. Feeds refresh hourly-to-daily. Article, topic, entity, glossary, and compare pages regenerate as content changes. Prefer the most specific page-level llms.txt when available.