> 统一信息源热点采集器——从 16+ 平台采集热门内容,生成结构化热点池
Scanned 9/5/2026
Install to Claude Code
npx -y skills add aAAaqwq/AGI-Super-Skills --skill content-source-aggregator --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Content Source Aggregator?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/aaaaqwq-content-source-aggregator-agi-super-team)More formats (shields.io, HTML) on the badges page.
# content-source-aggregator
> 统一信息源热点采集器——从 16+ 平台采集热门内容,生成结构化热点池
## 使用场景
- 每日多平台热点自动采集(微博/知乎/头条/抖音/B站/GitHub/YouTube/Twitter/Reddit/HackerNews 等)
- 内容管线上游数据源,为 content-factory 提供原始热点
- 海外源自动走代理(Clash),国内源直连
## 使用方法
```bash
# 采集所有平台
python ~/clawd/skills/content-source-aggregator/scripts/fetch_all.py
# 只采集指定平台
python fetch_all.py --source github
python fetch_all.py --source hackernews
# Dry run(只打印不保存)
python fetch_all.py --dry-run
```
## 支持平台(16+)
| 分类 | 平台 |
|------|------|
| 国内社交 | 微博、知乎、头条、抖音 |
| 国内社区 | B站、LinuxDo、小红书 |
| 海外社交 | Twitter/X、Reddit、YouTube |
| 开发者 | GitHub Trending、HackerNews、ArXiv、ProductHunt |
| 微信生态 | 微信公众号(搜狗)、微信视频号(无 API) |
## 配置要求
- Python 3.10+, curl
- 代理(海外源):`CONTENT_PROXY` 环境变量(默认 `http://127.0.0.1:7897`)
- Cookie 文件(可选):`~/.playwright-data/linuxdo/cookies.txt`、`xiaohongshu/cookies.txt` 等
- 配置文件:`scripts/config.json`(账号列表、subreddit、频道 ID、优先级等)
- 输出目录:`~/clawd/workspace/content-pipeline/hotpool/`
## 相关文件
- `scripts/fetch_all.py` — 采集主脚本
- `scripts/config.json` — 平台配置(账号、优先级等)
- `~/clawd/workspace/content-pipeline/hotpool/` — 热点池输出
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.