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Lowyat Forum Research

作者 Johnson · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install lowyat-forum-research
功能描述
Research any topic by searching Lowyat forum (forum.lowyat.net), scraping relevant threads into Excel, and analyzing the results. Use this skill whenever the...
使用说明 (SKILL.md)

Lowyat Forum Research Tool

End-to-end research pipeline: Search → Scrape → Analyze

Workflow

Step 1: Understand the user's research topic

  • Ask clarifying questions if needed (e.g. what specifically they want to learn)
  • Break the topic into 3-5 search keyword variations

Step 2: Search for relevant threads

  • Use WebSearch with site:forum.lowyat.net \x3Ckeywords> to find threads
  • Use allowed_domains: ["forum.lowyat.net"] to filter results
  • Run multiple searches in parallel with different keyword angles
  • Present the most relevant threads to the user with titles and URLs
  • Let the user pick which threads to scrape, or recommend the best ones

Step 3: Scrape the selected threads

  • The scraper script (datascraping.py) should be in the project root
  • Install Python dependencies:
pip install requests beautifulsoup4 html5lib openpyxl tqdm

Or if you have uv installed:

uv sync
  • Run the scraper for each thread:
python datascraping.py \x3CTOPIC_URL>
  • IMPORTANT: Do NOT include /all or /+N suffixes in the URL — just use the base topic URL (e.g. https://forum.lowyat.net/topic/5411252)
  • To scrape multiple threads, run them sequentially (one at a time) to be respectful to the server. Only run up to 3 in parallel if the user explicitly asks for speed, using & and wait
  • Output: \x3Ctopic_id>.xlsx files with columns: Name, Date, Comment

Step 4: Analyze the scraped data

  • Read the scraped .xlsx files to understand the forum discussions
  • Synthesize findings across all threads into a structured summary
  • Organize insights by the user's research questions
  • Include: consensus opinions, brand recommendations, price ranges, warnings, and specific user experiences
  • Cite which thread/user said what when relevant

Scraper Details

  • Forum uses 20 posts per page, paginated via /+N URL suffix
  • Scraper auto-detects total pages and crawls all of them
  • Random 0.5–2s delay between page requests
  • Saves incrementally after each page — safe to interrupt
  • If .xlsx already exists, it resumes by appending

Tips for good searches

  • Use brand names: site:forum.lowyat.net Toto toilet
  • Use Malay keywords too: site:forum.lowyat.net kipas exhaust tandas
  • Add "recommendation" or "review": site:forum.lowyat.net water heater recommendation
  • Search by location: site:forum.lowyat.net bathroom shop KL Selangor
  • Try year filters for recency: site:forum.lowyat.net smart toilet 2024 2025

Example usage

User: "I want to research mechanical keyboards on Lowyat"

  1. Search with variations: mechanical keyboard recommendation, cherry mx switch, keychron Malaysia, custom keyboard
  2. Present top threads to user
  3. Scrape selected threads in parallel
  4. Read the xlsx files and provide analysis: popular brands, price ranges, where to buy, common complaints

Links

Disclaimer

Scraped data contains publicly available usernames, dates, and comments from forum.lowyat.net. This tool is intended for personal research purposes only. Users are responsible for how they store, share, and use the scraped data in compliance with applicable privacy laws and Lowyat forum's terms of service.

安全使用建议
This skill appears to do what it says (scrape Lowyat threads into Excel), but before installing or running it consider: 1) Terms of Service & robots.txt — scraping may violate Lowyat's terms or local laws; verify permission. 2) Privacy — scraped data includes public usernames and timestamps; handle, store, and share it responsibly and anonymize if needed. 3) Load on the site — follow the documented delays and avoid bulk parallel scraping to prevent denial-of-service. 4) Environment setup — ensure you run the pip installs in a virtual environment and that your Python version meets pyproject (>=3.12) if you encounter issues. 5) Source verification — SKILL.md links to a GitHub repo; if provenance matters, inspect that repository for updates or additional code. If you need the agent to run this autonomously, be aware autonomous invocation plus data collection increases risk, so restrict usage accordingly.
功能分析
Type: OpenClaw Skill Name: lowyat-forum-research Version: 1.0.2 The skill bundle is a legitimate web scraping tool designed to extract and analyze forum posts from Lowyat.net. The Python script (datascraping.py) uses standard libraries like BeautifulSoup and requests to collect public forum data into Excel files, incorporating respectful scraping practices such as random delays and sequential processing. No evidence of data exfiltration, malicious execution, or prompt injection was found.
能力评估
Purpose & Capability
Name/description match the provided files and instructions. The included datascraping.py and SKILL.md implement exactly: search (via WebSearch guidance), scrape forum.lowyat.net pages, and save results to .xlsx. Required packages are proportional to the task (requests, BeautifulSoup, openpyxl, tqdm).
Instruction Scope
SKILL.md stays within scope: it instructs how to find threads, run the included scraper, and analyze the resulting Excel files. It does not request unrelated file reads, credentials, or remote endpoints beyond forum.lowyat.net. It explicitly recommends polite scraping behavior (delays, limited parallelism).
Install Mechanism
There is no automated install spec; SKILL.md asks the user to pip-install common Python libraries. No downloads from untrusted URLs or archive extraction are present. The code is included in the package (datascraping.py).
Credentials
The skill requests no environment variables or credentials. All external network activity is limited to the target forum pages. The pyproject specifies Python >=3.12 which is reasonable but not enforced by SKILL.md; this mismatch is minor and not a security risk.
Persistence & Privilege
Skill is not marked always:true and does not modify other skills or agent-wide configs. It runs as a user-invoked tool and does not request elevated system presence.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install lowyat-forum-research
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /lowyat-forum-research 触发
  4. 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
v1.0.2
- Cleaned up and simplified Python package installation instructions for the scraper. - Provided clearer guidance on using pip or uv for dependencies. - Removed detailed setup steps for uv and consolidated installation commands. - No changes to features or core workflow; documentation/editing updates only.
v1.0.1
- Added explicit requirement for the uv Python package manager; included install instructions. - Provided pip alternative for users who prefer it over uv. - Clarified that scrapes should be run sequentially (one at a time) to respect server load, with limited parallelism only if explicitly requested. - Added "required_binaries" section for uv in the manifest. - Included official project and ClawHub links, and a disclaimer about data usage and respect for privacy laws.
v1.0.0
Initial release — Lowyat Forum Research & Analysis tool: - Enables end-to-end research on any topic using the Lowyat forum: search, scrape, and analyze threads. - Searches forum.lowyat.net with multiple keyword variations and presents relevant threads for user selection. - Scrapes selected threads into Excel files with detailed post data (Name, Date, Comment). - Analyzes scraped data to extract consensus, recommendations, price info, and user experiences, organized by user research questions. - Includes clear setup and usage instructions for scraping and data handling. - Designed for Malaysian consumer research topics; triggers on relevant keywords automatically.
元数据
Slug lowyat-forum-research
版本 1.0.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

Lowyat Forum Research 是什么?

Research any topic by searching Lowyat forum (forum.lowyat.net), scraping relevant threads into Excel, and analyzing the results. Use this skill whenever the... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 106 次。

如何安装 Lowyat Forum Research?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install lowyat-forum-research」即可一键安装,无需额外配置。

Lowyat Forum Research 是免费的吗?

是的,Lowyat Forum Research 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Lowyat Forum Research 支持哪些平台?

Lowyat Forum Research 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 Lowyat Forum Research?

由 Johnson(@superoo7)开发并维护,当前版本 v1.0.2。

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