Cross-platform content distribution skills for indie creators — publish once to X, LinkedIn, WeChat, XiaoHongShu, Bilibili, Telegram. agent-reach, MediaCrawler, qiaomu publishers, and platform-specific MCPs.
Content Syndication tools are AI-powered software designed to help developers and teams tackle content syndication-related tasks more efficiently. These tools are typically published as open-source projects on GitHub and can be integrated into existing workflows via MCP (Model Context Protocol), Claude Skills, or standalone agent frameworks. On Agent Skills Hub, we index 25 quality-scored content syndication tools across languages including Python, Go, JavaScript.
In 2026, the AI agent ecosystem is maturing rapidly. Content Syndication tools can significantly boost development efficiency by automating repetitive tasks, reducing human error, and providing intelligent suggestions. The top 3 tools — Agent-Reach, MediaCrawler, last30days-skill — have earned an average of 10,722 GitHub stars, reflecting strong community validation. 20 of the listed tools come with clear open-source licenses, ensuring freedom to use and modify.
When choosing a content syndication tool, consider these factors: 1) Community activity — GitHub stars and recent commit frequency indicate reliability; 2) Integration method — check if it supports MCP, Claude, or your preferred agent framework; 3) Language compatibility — the most common language in this list is Python; 4) Quality score — Agent Skills Hub's composite score evaluates code quality, documentation completeness, and maintenance activity. Our recommendation: start with Agent-Reach — it ranks highest in both star count and quality score.
Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫
AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
Universal content grabber — fetch, normalize, and digest content from 7+ platforms (WeChat, XHS, X/Twitter, YouTube, Bilibili, Telegram, RSS)
A Browser Use Agent that actually reads social media. Fast. Precise. Deep.
AI agent skills for social media content strategy, creation, and analysis across text-first platforms
An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的 AI 社交媒体智能体——发现热点趋势、创作内容、一键发布至各大平台，并学习分析哪些内容真正有效，覆盖小红书、抖音、知乎、哔哩哔哩等平台。
Self-hosted RedNote, X/Twitter, and Douyin downloader for Docker/Unraid.
通用、模块化的自媒体内容生产与经营 Skills / A modular, tool-agnostic self-media content skill suite
🪧 Claude Code / Codex skill — generate Xiaohongshu carousels & WeChat 21:9+1:1 cover pairs. Editorial × Swiss visual systems, 28 layouts, 10 themes, single-file HTML → PNG. 小红书图文 + 公众号封面对
An agentic social media scheduling workspace engine/tool (CLI + Dashboard)
把Openclaw 变成小红书运营助手，帮你分析、选题、创作、复盘、复刻，甚至全面托管
TikHub API 助手是一个 Codex/Claude Code Agent Skill，用于帮助用户搜索、发现和调用 TikHub API。TikHub 提供了多平台社交媒体数据 API，支持抖音、TikTok、小红书、Instagram、YouTube、Twitter、Reddit 等平台。This is a TikHub API skill/documentation repository. TikHub is a multi-platform social media data API service that provides RESTful endpoints for platforms including Douyin (抖音), TikTok, Xiaohongshu
红狐数据（RedFoxHub） 技能合集：面向 Agent 的可复用 SKILL 集合，覆盖灵感、选题、文案创作、数据复盘等场景，持续更新。
Social media scheduling CLI and OpenClaw skill for AI agents posting to X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, and Pinterest.
AI-powered content production pipeline for creators. One prompt → multi-platform publishing. Claude Code Skill.
小红书图文内容工作台：把账号定位、热点研究、选题、原创文稿、品牌配图、预览和人工确认组织成一条可控流程。
Tampermonkey userscripts for WeChat, Douyin, and X content workflows
在 DeepSeek Harness / Claude Code / Cursor / Codex / Gemini CLI 里直接搜索 20 个中国开放平台的 65,600+ 篇 API 文档；零配置，支持 Skill 与 DSH 原生插件。
AI agent skills for social media research. Outlier posts, comment mining, competitor teardowns, ad libraries & trends across TikTok, Instagram, YouTube, Reddit, X, LinkedIn & more. Powered by ScrapeCreators. Works with Claude Code, Cursor, Codex, Gemini CLI.
```bash
npx skills add ScrapeCreators/social-media-research-skills
```✨ The agentic HTML editor — your local AI agent writes the HTML, you ship it. 🚀 75 Skills × 9 Surfaces (magazine · deck · poster · XHS / tweet · prototype · data report · Hyperframes) 🛡️ Sandboxed preview · 📤 1-click to WeChat / X / Zhihu / HTML / PNG 🔑 Zero API key — Claude Code / Cursor / Codex / Gemini / Copilot / OpenCode / Qwen / Aider.
发布前审｜发抖音/小红书/视频号前先让 AI 审一遍：哪句踩线、依据哪条官方规则、给能直接用的改法。38 篇真实样本校准判定尺度，80+ 条官方原文引文可查证，你踩过的坑沉淀成本地规则库越用越准。不承诺过审，不教绕审。
A Claude Code skill by Hao (駱君昊) that learns your Facebook voice and auto-posts to FB / IG / Threads / X with a 14-day content calendar. Mega-viral validated: 80K reach / 448 likes / 500 comments on first post. Includes Day 2 flop postmortem.
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| Agent-Reach | ★ 84.9k | Python | MIT | 80 |
| MediaCrawler | ★ 65.6k | Python | — | 71 |
| last30days-skill | ★ 62.4k | Python | MIT | 80 |
| xiaohongshu-mcp | ★ 15.9k | Go | Apache-2.0 | 77 |
| XHS-Downloader | ★ 12.8k | JavaScript | GPL-3.0 | 73 |
| feedgrab | ★ 609 | Python | MIT | 55 |
| socai | ★ 206 | Rust | Apache-2.0 | 64 |
| social-media-skills | ★ 402 | Shell | MIT | 71 |
| Easel | ★ 1.3k | Python | Apache-2.0 | 64 |
| rednote-downloader | ★ 74 | JavaScript | — | 70 |
| self-media-content-workflow | ★ 382 | Python | MIT | 81 |
| guizang-social-card-skill | ★ 7.2k | HTML | AGPL-3.0 | 65 |
| openquok-monorepo | ★ 70 | TypeScript | AGPL-3.0 | 58 |
| xiaohongshu-ops-skill | ★ 2.4k | — | — | 56 |
| tikhub_api_skill | ★ 118 | Python | — | 72 |
| redfox-community | ★ 410 | Python | — | 73 |
| socialclaw | ★ 82 | JavaScript | MIT | 67 |
| content-pipeline | ★ 213 | TypeScript | MIT | 67 |
| agent-xiaohongshu-workbench | ★ 116 | JavaScript | MIT | 63 |
| qiaomu-userscripts | ★ 124 | JavaScript | MIT | 59 |
| SpecFusion | ★ 66 | TypeScript | MIT | 60 |
| social-media-research-skills | ★ 2.7k | Python | MIT | 72 |
| html-anything | ★ 8.8k | HTML | Apache-2.0 | 76 |
| yuwen-publish-precheck | ★ 739 | Python | MIT | 82 |
| claude-skill-social-post | ★ 674 | JavaScript | MIT | 74 |
The top content syndication tools in 2026 are Agent-Reach, MediaCrawler, last30days-skill. Agent Skills Hub ranks 25 options by GitHub stars, quality score (6 dimensions including completeness, examples, and agent readiness), and recent activity. The list is rebuilt every 8 hours from live GitHub data.
Agent-Reach (84.9k stars) is the most adopted choice for general content syndication workflows, written in Python. MediaCrawler (65.6k stars) is a strong alternative. Pick by your existing stack: match the language and runtime your team already uses to minimize integration cost. If unsure, start with Agent-Reach — it has the deepest community and the most examples online.
Avoid pre-built content syndication tools when (1) your use case requires deep customization that the tool's plugin system doesn't support, (2) you have strict compliance requirements that ban third-party dependencies, (3) the tool's maintenance is inactive (last commit >6 months ago), or (4) your data volume is small enough that a 50-line custom script is cheaper than learning the tool. For most production workflows above 100 requests/day, the time savings from a maintained tool outweigh the customization loss.
Content Syndication focuses specifically on cross-platform content distribution skills for indie creators — publish once to x, linkedin, wechat, xiaohongshu, bilibili, telegram. agent-reach, mediacrawler, qiaomu publishers, and platform-specific mcps. Telegram Bot is a related but distinct category — see https://agentskillshub.top/best/telegram-bot/ for those tools. The two often appear in the same agent pipeline but solve different problems: choose content syndication when your primary goal is the specific task, and telegram bot when the workflow is broader.
For most teams, yes. Agent-Reach has 84.9k stars worth of community testing, handles edge cases you haven't thought of, and ships with documentation. Build your own only when (1) your requirements are deeply non-standard, (2) you have a security/compliance reason to avoid OSS dependencies, or (3) the maintenance burden is small enough (<200 lines of code) that you'll save time long-term. The break-even point is usually around 2-3 weeks of dev time saved.
Most content syndication tools listed are open source under permissive licenses (MIT, Apache 2.0). A handful offer paid managed/cloud versions on top of free self-hosted core. Always check the LICENSE file on each tool's GitHub repository before commercial use — some use AGPL or non-commercial restrictions that may not fit your deployment model.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: