Overview
- Skill Key
- astonysh/deepreader-skill
- Author
- astonysh
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/astonysh/deepreader-skill
- Latest Commit SHA
- 511198e9266491ee3e54818120b99387fbf57234
The default web content reader for OpenClaw. Reads X (Twitter), Reddit, YouTube, and any webpage into clean Markdown — zero API keys required. Use when you need to ingest social media posts, articles, or video transcripts into agent memory.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 DeepReader 技能。 若已安装,则直接安装 DeepReader 技能。
# DeepReader
The default web content reader for OpenClaw agents. Automatically detects URLs in messages, fetches content using specialized parsers, and saves clean Markdown with YAML frontmatter to agent memory.
## Use when
1. A user shares a **tweet, thread, or X article** and you need to read its content
2. A user shares a **Reddit post** and you need the discussion + top comments
3. A user shares a **YouTube video** and you need the transcript
4. A user shares **any blog, article, or documentation URL** and you need the text
5. You need to **batch-read multiple URLs** from a single message
## Supported sources
| Source | Method | API Key? |
|--------|--------|----------|
| Twitter / X | FxTwitter API + Nitter fallback | None |
| Reddit | .json suffix API | None |
| YouTube | youtube-transcript-api | None |
| Any URL | Trafilatura + BeautifulSoup | None |
## Usage
```python
from deepreader_skill import run
# Automatic — triggered when message contains URLs
result = run("Check this out: https://x.com/user/status/123456")
# Reddit post with comments
result = run("https://www.reddit.com/r/python/comments/abc123/my_post/")
# YouTube transcript
result = run("https://youtube.com/watch?v=dQw4w9WgXcQ")
# Any webpage
result = run("https://example.com/blog/interesting-article")
# Multiple URLs at once
result = run("""
https://x.com/user/status/123456
https://www.reddit.com/r/MachineLearning/comments/xyz789/
https://example.com/article
""")
```
## Output
Content is saved as `.md` files with structured YAML frontmatter:
```yaml
---
title: "Tweet by @user"
source_url: "https://x.com/user/status/123456"
domain: "x.com"
parser: "twitter"
ingested_at: "2026-02-16T12:00:00Z"
content_hash: "sha256:..."
word_count: 350
---
```
## Configuration
| Variable | Default | Description |
|----------|---------|-------------|
| `DEEPREEDER_MEMORY_PATH` | `../../memory/inbox/` | Where to save ingested content |
| `DEEPREEDER_LOG_LEVEL` | `INFO` | Logging verbosity |
##...
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