Tencent SkillHub · Content Creation

Trakt.tv Integration

Track and recommend TV shows and movies using Trakt.tv. Use when the user asks for show/movie recommendations, wants to track what they're watching, check their watchlist, or get personalized suggestions based on their viewing history. Requires Trakt.tv account with Pro subscription for full functionality.

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: INSTALL.md, README.md, SKILL.md, references/api.md, requirements.txt, scripts/setup.py

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

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New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.1.0

Provenance

Publisher: fr3nch13
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 20 sections Open source page

Trakt.tv Integration for OpenClaw

Integrate with Trakt.tv to track watch history and provide personalized show/movie recommendations. 📚 Trakt API Documentation: https://trakt.docs.apiary.io/

First-Time Setup Required

Before using this skill, run the interactive setup:

Automated Setup (Recommended)

python3 scripts/setup.py This will guide you through: Installing dependencies Creating a Trakt application Configuring credentials Authenticating with PIN Testing the integration

Manual Setup

If automated setup doesn't work, follow the manual steps in the Setup section below.

Interactive Setup for OpenClaw

When a user asks to "install Trakt" or "set up Trakt integration," OpenClaw should: Read INSTALL.md for detailed interactive flow Or run python3 scripts/setup.py and guide user through prompts

Features

Track watch history (automatically synced by Trakt from streaming services) Get personalized recommendations based on viewing habits Access user watchlists and collections Search for shows and movies View trending content

Prerequisites

Python dependencies: # Install via pip (with --break-system-packages if needed) pip3 install requests # OR use a virtual environment (recommended) python3 -m venv ~/.openclaw-venv source ~/.openclaw-venv/bin/activate pip install requests Alternatively, install via Homebrew if available: brew install python-requests Trakt.tv account with Pro subscription (required for automatic watch tracking) Trakt API application - Create at https://trakt.tv/oauth/applications Configuration file: ~/.openclaw/trakt_config.json (see setup below)

1. Create Trakt Application

Visit https://trakt.tv/oauth/applications Click "New Application" Fill in the form: Name: "OpenClaw Assistant" Description: "Personal AI assistant integration" Redirect URI: urn:ietf:wg:oauth:2.0:oob (for PIN auth) Permissions: Check all that apply Save and note your Client ID and Client Secret

2. Create Configuration File

Create ~/.openclaw/trakt_config.json with your credentials: { "client_id": "YOUR_CLIENT_ID_HERE", "client_secret": "YOUR_CLIENT_SECRET_HERE", "access_token": "", "refresh_token": "" } Replace YOUR_CLIENT_ID_HERE and YOUR_CLIENT_SECRET_HERE with your actual values from step 1. Note: Leave access_token and refresh_token empty - they'll be filled automatically after authentication.

3. Authenticate

Run the authentication script: python3 scripts/trakt_client.py auth This will output a PIN URL. Visit it, authorize the app, and run: python3 scripts/trakt_client.py auth <PIN> Authentication tokens are saved to ~/.openclaw/trakt_config.json

Get Recommendations

When a user asks for show/movie recommendations: python3 scripts/trakt_client.py recommend This returns personalized recommendations based on the user's watch history and ratings.

Check Watch History

python3 scripts/trakt_client.py history Returns the user's recent watch history.

View Watchlist

python3 scripts/trakt_client.py watchlist Shows content the user has saved to watch later.

Search

python3 scripts/trakt_client.py search "Breaking Bad" Search for specific shows or movies.

Recommendation Workflow

When a user asks "What should I watch?" or similar: Get personalized recommendations: python3 scripts/trakt_client.py recommend Parse the results and present them naturally: Show title, year, rating Brief description/genre Why it's recommended (if available) Optionally check watchlist to avoid suggesting shows they already plan to watch Consider recent history to avoid re-suggesting recently watched content

API Reference

See references/api.md for detailed Trakt API endpoint documentation.

Common Use Cases

"What should I watch tonight?" Get recommendations, filter by mood/genre if specified Check trending if user wants something popular "Add [show] to my watchlist" Search for the show Add to Trakt watchlist (requires additional endpoint implementation) "What have I been watching lately?" Get watch history Summarize recent shows/movies "Is [show] trending?" Get trending list Search for specific show

Limitations

Trakt Pro subscription required for automatic watch tracking from streaming services Recommendations improve over time as watch history grows API rate limits apply: 1000 requests per 5 minutes (authenticated) Full API documentation: https://trakt.docs.apiary.io/

Troubleshooting

"Authentication failed" Verify CLIENT_ID and CLIENT_SECRET are set correctly in ~/.openclaw/trakt_config.json Ensure PIN is copied accurately (case-sensitive) Check that your Trakt application has proper permissions "No recommendations returned" User may not have enough watch history yet Try falling back to trending content Ensure user has rated some content on Trakt "API request failed" Check authentication token hasn't expired Verify network connectivity Check Trakt API status: https://status.trakt.tv

Category context

Writing, remixing, publishing, visual generation, and marketing content production.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

4 Docs1 Scripts1 Files

SKILL.md Primary doc
INSTALL.md Docs
README.md Docs
references/api.md Docs
scripts/setup.py Scripts
requirements.txt Files