X Ingest Agent Skill

by chubbyguan

> X(Twitter) 推文采集 → 统一 frontmatter Markdown。自动区分图文与视频：图文下载图片本地嵌入，视频提取直链转成文字稿。无需登录（走官方嵌入端点）。

5k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

588

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/chubbyguan/chubbyskills --skill x-ingest

The instruction itself

1 sections, as written by the author

X(Twitter) 推文采集 Skill

把 X 推文抓成结构化 Markdown 入库。自动区分图文与视频笔记：图文 → 下载图片本地嵌入；

视频 → 像抖音那样转成文字稿。通过 X 官方嵌入用的 syndication 端点采集，无需登录、无需 API Key。

环境要求

# 图文采集零依赖（仅 Python 标准库）

# 视频推文转录需要（与抖音/B站/小红书同一套依赖）：
pip install funasr modelscope torch torchaudio
# macOS: brew install ffmpeg   |   Ubuntu: sudo apt install ffmpeg

使用方法

# 采集推文 → 统一 frontmatter Markdown
python scripts/fetch_tweet.py "https://x.com/user/status/1234567890" -o ./out
python scripts/fetch_tweet.py "https://twitter.com/user/status/1234567890" -o ./out

python scripts/fetch_tweet.py "链接" -o ./out --no-images   # 图文：只留图片链接不下载
python scripts/fetch_tweet.py "链接" -o ./out --no-video    # 视频：不转录，只留视频链接
python scripts/fetch_tweet.py "链接" -o ./out --fallback-text 手动正文.txt

产出

fetch_tweet.py → 统一 frontmatter Markdown（platform: x，含 note_type: image|video|text|article），含作者(name @handle)、互动数据（赞/回复）、话题标签。按内容类型分流：

图文 / 纯文字推文：正文 + 图片下载到本地 <标题>.assets/ 并以 ! 嵌入；--no-images 只留链接，单张失败自动回退为链接
视频推文：提取最高码率 mp4 直链 → ffmpeg 抽音频 → SenseVoice 转录（language=auto，X 中英混杂）写入 ## 视频文字稿；--no-video 只留视频链接；缺 funasr/ffmpeg 时自动降级为存链接
X 长文章（Article）：取文章标题、预览正文、封面图（封面本地化嵌入）。⚠️ syndication 不返回长文章全文，全文需登录另抓——Markdown 会标注「预览，全文见原文链接」

⚠️ 关于可用性

采集走 cdn.syndication.twimg.com/tweet-result——X 官方嵌入推文用的公开端点，无需登录，但它是非官方契约：

受保护账号、已删除、成人/受限内容可能取不到
端点或 token 算法（fetch_tweet.py 里的 make_token）若被 X 调整，需相应更新
目前仅支持单条推文；thread（连串推文）是未来增强方向

抓取失败时可以使用 --fallback-text：把浏览器里能看到的正文复制到 txt/md 文件，脚本仍会生成统一 frontmatter 的 Markdown，保证后续 content-enrich / 入库工作流不断。

合规声明

仅供个人学习与研究使用。请遵守 X 服务条款，控制请求频率，不要用于批量抓取、商用爬取或侵犯他人权益的场景。

衔接工作流

采集产物 → knowledge-base-management 入库（统一 frontmatter，按 platform 聚合）
海外信息源 → 配合 industry-intelligence-radar 的 X 信号扫描，沉淀情报
视频文字稿 → learning-notes-automation 提取知识点 + 闪卡

参考

X 官方嵌入（syndication）端点
FunAudioLLM/SenseVoice — 语音识别模型

Other skills for the same job

different authors, same section of the catalogue

Canvas Design

by anthropics

vendor ×13

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

13k tokens

How to use it

Copy the folder

Take chubbyguan/x-ingest from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, brew. Without those the skill loads but fails at the first command.