Track Your Movie Obsession with the Letterboxd Companion Skill

If you're a film buff who logs every movie on Letterboxd, you know the drill: open the app, scroll through your diary, check your watchlist. But what if your AI agent could do that for you? The Letterboxd Companion skill brings Letterboxd data straight into your Clawdbot workflow—no browser required.

What Is This Skill?

The Letterboxd Companion (slug: letterboxd-tracker) is a read-only integration that lets your AI agent fetch:

• Profile stats: How many films you've watched, your reviews, lists, and favorites
• Diary entries: Your recent watch history
• Watchlist: Movies you're planning to see
• Movie details: Directors, year, rating, and descriptions for any film

It uses the letterboxdpy Python library to scrape public Letterboxd data—no API key required.

Installation

Getting started takes about 30 seconds:

clawdhub install letterboxd-tracker

The skill requires one Python dependency:

pip install letterboxdpy

That's it. No API keys, no OAuth flows, no configuration files.

Core Commands

The skill exposes four commands your agent can call:

1. User Profile (lb_user)

Get stats for any Letterboxd user:

python lb_tool.py user "filmfanatic"

Returns watched count, review count, list count, and favorite films.

2. Diary (lb_diary)

Fetch recently watched movies:

python lb_tool.py diary "filmfanatic" 20

The second argument limits results (default: 10).

3. Watchlist (lb_watchlist)

See what's in the queue:

python lb_tool.py watchlist "filmfanatic" 15

4. Movie Details (lb_movie)

Look up any film by its Letterboxd slug:

python lb_tool.py movie "the-godfather"

Returns title, year, directors, average rating, and description.

Real-World Usage

Once installed, just ask your agent naturally:

• "How many movies have I watched this year?"
• "What's on my Letterboxd watchlist?"
• "Tell me about the movie Oppenheimer"
• "What did I watch last month?"

The agent will call the appropriate command and present the results.

Example Workflow

Want a weekly movie recap? Combine this with Clawdbot's cron feature:

Or build a recommendation flow: "Look at my recent watches and suggest something similar from my watchlist."

Tips & Gotchas

Finding movie slugs: The slug is the URL portion after /film/. For "The Batman" (2022), the URL is letterboxd.com/film/the-batman/, so the slug is the-batman.

Username matters: All commands except lb_movie require a username. If you always query the same account, consider storing it in your agent's memory.

Rate limiting: Since this scrapes public pages, rapid queries might get throttled. Space out bulk requests.

Public profiles only: The skill can only access public Letterboxd data. Private profiles won't work.

Security

ClawdHub's security scan rates this skill as Benign with high confidence. It's read-only, requires no credentials, and makes no unusual network calls. Still, as with any skill that fetches external data, review the code if you're curious: it's just ~200 lines of Python.

Conclusion

The Letterboxd Companion is a simple, focused skill that does one thing well: connects your movie-watching life to your AI agent. No complex setup, no API management—just install and start asking about films.

Install it: clawdhub install letterboxd-tracker

View on ClawdHub: clawhub.ai/tamil-9421/letterboxd-tracker

Got ideas for how you'd use this? Drop a comment below.