social-reader

# 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

```bash
pip install requests
```

## Configuration Files

| File | Purpose |
|------|---------|
| `prompt.txt` | LLM system prompt for the Processor node |
| `sources.json` | List of monitored accounts and fetch intervals (pipeline mode) |
| `input_urls.txt` | Manually entered post URLs (one per line, `#` for comments) |
| `seen_ids.json` | Deduplication cache for seen post IDs (pipeline mode only) |
| `pending_tweets.json` | Queue of unprocessed posts from the Watcher |
| `drafts.json` | LLM-distilled drafts from the Processor |
| `archive.json` | Archived history records |

### Environment Variables (required only for Pipeline Mode Processor)

| Variable | Description | Default |
|----------|-------------|---------|
| `LLM_API_KEY` | LLM API key (required) | None |
| `LLM_BASE_URL` | API endpoint | `https://api.openai.com/v1` |
| `LLM_MODEL` | Model name | `gpt-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

```python
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["conte...