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asdsadasd
作者
Phan Văn Năng
· GitHub ↗
· v1.0.0
· MIT-0
207
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当前安装
1
版本数
在 OpenClaw 中安装
/install asdsadasd
功能描述
An end-to-end AI Content Pipeline that crawls articles, rewrites them using Google Gemini, and automatically publishes to Facebook Fanpage.
使用说明 (SKILL.md)
🤖 OpenClaw AI Content Pipeline (Analyze + Publish)
Purpose
This is a production-ready OpenClaw Skill that merges a Web Crawler, an AI Rewriter (Google Gemini), and a Facebook Auto-Publisher into one seamless pipeline. It reads URLs (news articles or Facebook posts), rewrites them into engaging social media captions, and posts them directly to your Fanpage.
Core Capabilities
- Analyze Mode: Extracts data from URLs via Python
requests/BeautifulSoup(for static news) orApify(for JS-heavy content like Facebook). Generates localized rewritten text via Gemini 2.5 Flash. - Publish Mode: Pushes the generated content directly to a Facebook Page via Graph API v21.0.
- Batch Processing: Can ingest URLs line-by-line from a text file, process them in bulk, and save JSON reports.
Architecture Map
run.bat/main.py← Central Orchestrators (CLI Entry points)agents/crawler_agent.py← Hybrid Crawler (Native + Apify API)agents/writer_agent.py← AI Content Generator (Gemini Integration)agents/fb_publisher_agent.py← Graph API Poster (Messages & Images)config.py← Environment Loader & System Validation
Setup & Environment
Ensure you create a .env file at the root with the following variables:
# AI Models
GEMINI_API_KEY=...
OPENAI_API_KEY=... # Optional: For DALL-E 3 image generation
# Scraping
APIFY_API_TOKEN=...
# Facebook Graph API
FB_APP_ID=...
FB_APP_SECRET=...
FB_PAGE_ID=...
FB_PAGE_ACCESS_TOKEN=...
Usage commands
From your terminal, run the following commands (Windows run.bat wrappers):
1. Analyze (Test scrape and text rewrite)
# Analyze a single URL
run.bat analyze "https://vnexpress.net/..."
# Analyze and save as JSON
run.bat analyze "https://dantri.com.vn/..." --save
# Batch analyze from a text file
run.bat analyze-file urls.txt
2. Publish (Post directly to Facebook)
# Test Graph API Token connection
run.bat test
run.bat test-post
# Full pipeline (Crawl -> Rewrite -> Post to Fanpage)
run.bat run "https://dantri.com.vn/..."
# Pipeline dry-run (No actual post)
run.bat dry "https://dantri.com.vn/..."
安全使用建议
Do not install or run this skill on any account containing real, valuable credentials until you address the issues below: 1) The repository includes a .env file with what look like real API keys and a Facebook page access token — treat these as compromised. If you or your org used these keys, rotate/revoke them immediately. 2) Remove any secrets from the codebase and ensure .env is listed in .gitignore before using; provide your own credentials at runtime instead. 3) Inspect SKILL.md and code for the flagged base64/prompt-injection block and review any encoded or obfuscated content; decode and verify intent before running. 4) Review fb_token_helper.py behavior (it will walk you through exchanging tokens) and ensure the Page token scopes/permissions are appropriate and limited. 5) Run the code in a sandboxed environment with disposable test accounts (Facebook test pages, sandbox API keys) and monitor outbound network calls. 6) If you want to proceed after remediation: remove committed secrets, audit the code for hidden endpoints or exfiltration, and limit tokens to least privilege. If you need, I can: a) point to exact lines/files with secrets and how to sanitize them, b) summarize the fb_token_helper.py flow, or c) suggest a safe test checklist.
功能分析
Type: OpenClaw Skill
Name: asdsadasd
Version: 1.0.0
The bundle contains a `.env` file with multiple hardcoded, active API keys for OpenAI, Apify, and Facebook (including `FB_APP_SECRET` and `FB_PAGE_ACCESS_TOKEN`). While the Python logic in `main.py` and the various agents (e.g., `fb_publisher_agent.py`, `writer_agent.py`) appears to align with the stated purpose of an automated AI content pipeline, the distribution of live credentials is a critical security risk. No evidence of intentional data exfiltration or backdoors was found, but the presence of these secrets in a distributable package is highly irregular and potentially dangerous.
能力评估
Purpose & Capability
The name/description (AI crawl + Gemini rewrite + Facebook publish) maps to the provided code: crawler, writer (Gemini), image generator (OpenAI DALL·E optional), and Facebook publisher. Declared env vars in SKILL.md (Gemini, Apify, FB app/page tokens) align with the functionality. Minor inconsistency: SKILL.md frontmatter lists required envs but README/.env include additional keys (OPENAI_API_KEY, FB_CLIENT_TOKEN) which the code loads (OPENAI_API_KEY is optional for images).
Instruction Scope
Runtime instructions ask you to create/use a .env with credentials and run helper scripts (fb_token_helper.py) and the pipeline. The repository as packaged already contains a .env file with real-looking secrets and a large output_log — that means sensitive credentials are bundled and could be reused or leaked. A pre-scan pattern flagged a base64-block in SKILL.md (possible prompt-injection). The instructions do not appear to call external endpoints beyond the declared services, but the presence of committed secrets and injection indicators elevates risk.
Install Mechanism
No install spec is provided (instruction-only skill), and dependencies are standard Python packages listed in requirements.txt. There are no downloads from arbitrary URLs or archive extraction steps in the manifest. Risk here is from running included Python code (which may call network APIs) rather than from an installer payload.
Credentials
The skill legitimately needs API tokens for Gemini, Apify, and Facebook; those are declared. However, the package contains a .env file with actual credentials (OpenAI key, Apify token, FB_APP_SECRET, FB_PAGE_ACCESS_TOKEN) committed in the manifest — this is disproportionate and unsafe. Including working secrets in the repository is unexpected for a distributed skill and presents high risk (leaked/compromised credentials).
Persistence & Privilege
The skill is not always-included and is user-invocable (normal). There is a sitecustomize.py that modifies Python stdout encoding; sitecustomize is auto-imported by Python when on sys.path, which is a modest scope change but not inherently malicious. The skill does not request elevated system persistence or modify other skills' config.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install asdsadasd - 安装完成后，直接呼叫该 Skill 的名称或使用
/asdsadasd触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
ai-content-pipeline 2.0.0 introduces an all-in-one automated workflow for AI-based article rewriting and social media publishing.
- Combines web crawling, AI rewriting (Google Gemini), and Facebook posting into a seamless pipeline.
- Supports extraction from both static news sites and dynamic content (e.g., Facebook) using BeautifulSoup or Apify.
- Generates engaging, localized captions automatically via Gemini 2.5 Flash.
- Enables batch processing of URLs and JSON reporting.
- Simple command-line interface for analyzing, rewriting, and posting content directly to your Facebook Fanpage.
- Configuration via `.env` file for API and platform integration.
元数据
常见问题
asdsadasd 是什么？
An end-to-end AI Content Pipeline that crawls articles, rewrites them using Google Gemini, and automatically publishes to Facebook Fanpage. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 207 次。
如何安装 asdsadasd？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install asdsadasd」即可一键安装，无需额外配置。
asdsadasd 是免费的吗？
是的，asdsadasd 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
asdsadasd 支持哪些平台？
asdsadasd 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 asdsadasd？
由 Phan Văn Năng（@yunneetoichoi）开发并维护，当前版本 v1.0.0。
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