A powerful integration that enables AI agents to search multiple torrent indexers via Jackett's Torznab API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install jackett
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install jackett using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Jackett Search Integration?
This skill provides a robust interface for interacting with Jackett, a proxy server that translates queries into tracker-specific requests. By utilizing Openclaw Skills, developers can enable AI agents to browse, filter, and retrieve media releases across dozens of configured indexers simultaneously. It streamlines the process of finding specific media formats, resolutions, and editions by abstracting the complexities of Torznab XML feeds into clean, actionable data.
The tool is designed to optimize search efficiency by encouraging query normalization and scene-standard keyword usage. Whether you are looking for specific software distributions or high-fidelity media, this Openclaw Skills implementation ensures that agents can navigate the torrent ecosystem with precision and speed.
Jackett Search Integration Use Cases
- Automated searching for specific Linux ISOs or software releases across multiple public and private indexers.
- Finding high-quality media releases such as 4K, Remux, or HDR content using scene-style keywords.
- Monitoring specific indexers for new book or music releases to keep digital libraries up to date.
- Programmatically listing and inspecting the capabilities of configured Torznab indexers within a larger automation workflow.
How Jackett Search Integration Works
- The AI agent receives a request to find a specific file or media release through Openclaw Skills.
- The skill runner initializes the Jackett API script using credentials stored in the local configuration file.
- The skill normalizes the search query into scene-standard keywords, such as converting natural language into technical tokens like 2160p or x265.
- A request is sent to the Jackett server's Torznab endpoint, targeting either a specific indexer or an aggregate search.
- The skill parses the incoming XML response into a structured JSON format, including vital metadata like seeder counts and file sizes.
- The filtered results are presented back to the agent or passed to a subsequent automation stage for further processing.
Jackett Search Integration Setup
To get started with this skill, ensure your Jackett instance is running and accessible. Create the configuration file at ~/.openclaw/credentials/jackett/config.json with your connection details:
{
"url": "http://localhost:9117",
"apiKey": "your-jackett-api-key"
}
You can then verify your setup by listing all configured indexers using the following command:
./scripts/jackett-api.sh indexers --configured true
Jackett Search Integration Data Schema & Taxonomy
The skill provides structured JSON output to ensure compatibility with other Openclaw Skills. The schema includes metadata for pagination and detailed arrays for each result.
| Object | Field | Description |
|---|---|---|
| meta | total | Total results available on the indexer |
| meta | limit | The maximum number of results returned in this batch |
| results | title | The full name of the release |
| results | size | The file size in bytes |
| results | seeders | Number of active uploaders |
| results | download_url | The direct link to the torrent file or magnet |
| results | ids | External IDs including IMDB, TMDB, and TVDB |
Jackett Search Integration Advanced Features
- Support for typed searches including movie, tvsearch, music, and book categories for more accurate indexing.
- Advanced indexer filtering using tags such as
tag:public,lang:ento refine search sources. - Customizable output windowing using limit and offset parameters to manage large data sets within Openclaw Skills.
- Raw XML mode for power users who need to access the original Torznab response for complex metadata extraction.
SKILL.md
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