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social-reader

Social media content scraping and automation skill. Supports real-time single post reading, as well as scheduled batch patrol, LLM distillation, and review n...

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Social media content scraping and automation skill. Supports real-time single post reading, as well as scheduled batch patrol, LLM distillation, and review n...

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: archive.json, drafts.json, fetcher.py, input_urls.txt, notifier.py, pending_tweets.json

Validation

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Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: HackSing
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 10 sections Open source page

Social Reader Skill

This skill provides a social media content scraping and monitoring workflow. It offers two usage modes: Interactive Mode: Agent fetches a single post in real-time for reading, discussion, or reply generation within a conversation. Pipeline Mode: Background batch patrol of sources, with LLM distillation and review notifications.

Dependencies

pip install requests

Configuration Files

FilePurposeprompt.txtLLM system prompt for the Processor nodesources.jsonList of monitored accounts and fetch intervals (pipeline mode)input_urls.txtManually entered post URLs (one per line, # for comments)seen_ids.jsonDeduplication cache for seen post IDs (pipeline mode only)pending_tweets.jsonQueue of unprocessed posts from the Watcherdrafts.jsonLLM-distilled drafts from the Processorarchive.jsonArchived history records

Environment Variables (required only for Pipeline Mode Processor)

VariableDescriptionDefaultLLM_API_KEYLLM API key (required)NoneLLM_BASE_URLAPI endpointhttps://api.openai.com/v1LLM_MODELModel namegpt-4o-mini

Mode 1: Agent Interactive Call (Recommended)

When a user sends a social media post link and asks you to "read and discuss" or "generate a quality reply", call fetcher.py directly — do NOT use run_pipeline.py. run_pipeline.py triggers deduplication cache, fixed LLM distillation, and browser popups, which are unsuitable for interactive scenarios.

Usage Example

import sys skill_dir = r"d:\AIWareTop\Agent\openclaw-skills\social-reader" if skill_dir not in sys.path: sys.path.append(skill_dir) from fetcher import get_tweet result = get_tweet("https://x.com/user/status/123456") if result.get("success"): content = result["content"] # Now you can discuss the content with the user or generate a reply

get_tweet() Return Structure

{ "source": "fxtwitter", "success": true, "type": "tweet", "content": { "text": "Post body text", "author": "Display name", "username": "Username handle", "created_at": "Publish time", "likes": 123, "retweets": 45, "views": 6789, "replies": 10, "media": ["image_url_1", "image_url_2"] } } When type is "article" (long-form post), content additionally contains: title: Article title preview: Preview text full_text: Full article body (Markdown format) cover_image: Cover image URL This call is completely stateless — it writes no cache files and triggers no notification services.

Mode 2: Background Pipeline Batch Processing

Use run_pipeline.py to chain Watcher → Processor → Action nodes. Suitable for scheduled tasks or batch processing.

Three Core Nodes

Watcher (watcher.py) Reads input_urls.txt or sources.json, deduplicates via seen_ids.json, writes new posts to pending_tweets.json. Processor (processor.py) Reads pending_tweets.json, calls LLM to generate commentary, outputs to drafts.json. Requires LLM_API_KEY environment variable. Action (notifier.py) Starts a local HTTP review server (port 18923), opens a browser review page with approve/reject/rewrite/archive controls.

CLI Examples

# Full pipeline python run_pipeline.py # Specific URL python run_pipeline.py https://x.com/elonmusk/status/123456 # Single node execution python run_pipeline.py --watch-only python run_pipeline.py --process-only python run_pipeline.py --notify-only

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

3 Config2 Scripts1 Files

fetcher.py Scripts
notifier.py Scripts
archive.json Config
drafts.json Config
pending_tweets.json Config
input_urls.txt Files