A high-performance integration for monitoring, searching, and extracting real-time content from the HackerNews platform via its official API.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hn-reader
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install hn-reader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The HackerNews skill provides a bridge between your automated workflows and the tech community's pulse. By utilizing this within Openclaw Skills, developers and AI agents can programmatically fetch top stories, latest submissions, and trending discussions. It abstracts the official Firebase API into simple commands, making it easier to ingest community-driven tech news, Job postings, and Ask HN threads directly into your environment.
This skill is designed for efficiency and speed, requiring no authentication while providing deep access to the HN ecosystem. Whether you are building a news aggregator or a market research bot, this addition to your Openclaw Skills library ensures you stay informed with the most relevant tech data.
Integrating this into your project is straightforward as it leverages the public API. Ensure you have a Node.js environment ready to execute the skill commands within your Openclaw Skills workflow.
# Clone the repository and enter the skill directory
cd hackernews-skill
# Fetch the top 10 stories from the front page
node index.js top
# Search for specific technology trends
node index.js search "rust"
The skill returns structured data based on the HN Firebase schema, ensuring compatibility across different Openclaw Skills implementations:
| Attribute | Description | Data Type |
|---|---|---|
| ID | Unique identifier for the item | Integer |
| Title | The headline of the story or post | String |
| URL | The link to the external article | String |
| Score | Total points/upvotes received | Integer |
| By | The username of the author | String |
| Type | Category (story, job, comment, ask, show) | String |
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