A high-performance, trie-based word discovery tool for 4x4 Boggle grids supporting English and German dictionaries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install boggle
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 boggle 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 Boggle Solver?
The Boggle Solver is a robust utility designed for the Openclaw Skills library to identify all valid words within a 4x4 letter grid. Unlike standard AI models that may generate non-existent words, this skill uses a dictionary-only matching system to ensure 100% accuracy. It leverages a fast trie-based Depth First Search (DFS) algorithm to prune search paths instantly, making it ideal for competitive play or automated puzzle solving.
This tool is specifically optimized for developers and enthusiasts who need a reliable way to process word game data. By integrating with Openclaw Skills, users can bridge the gap between visual inputs—like photos of a game board—and verified textual results. It includes comprehensive support for both English (359K words) and German (1.35M words) vocabularies, presenting results in separate, clearly labeled sections.
Boggle Solver Use Cases
- Automatically solving Boggle puzzles from uploaded photos of physical game boards.
- Validating high-score word lists for competitive word game training.
- Providing a reliable backend for word-based puzzle applications within the Openclaw Skills ecosystem.
- Enhancing AI agent capabilities to handle multi-language word discovery tasks.
How Boggle Solver Works
- The skill receives a 4x4 grid input, typically extracted from a photo or provided as a string of 16 letters.
- The system confirms the grid layout with the user to ensure data integrity before processing.
- A trie data structure is built from the bundled dictionary files (performed once during the initial run).
- The solver initiates a Depth First Search (DFS) from every cell in the grid, exploring all 8 neighboring directions.
- Paths are pruned in real-time if they do not match a valid prefix in the trie, ensuring a solve time of less than 5ms.
- The skill runs independent passes for English and German, then outputs the results categorized by language and score.
Boggle Solver Setup
To use this solver within the Openclaw Skills environment, ensure you have Python 3 installed. The dictionaries will auto-download on the first execution. Use the following commands to solve a board:
# Solve using rows as arguments (English)
python3 skills/boggle/scripts/solve.py ABCD EFGH IJKL MNOP --lang en
# Solve using the full letter string (German)
python3 skills/boggle/scripts/solve.py --letters ABCDEFGHIJKLMNOP --lang de
Boggle Solver Data Schema & Taxonomy
The skill manages two primary dictionary files and can output structured JSON data for integration with other Openclaw Skills components.
| File Name | Language | Word Count |
|---|---|---|
| words_english_boggle.txt | English | 359,000 |
| words_german_boggle.txt | German | 1,350,000 |
Standard scoring rules applied:
- 3-4 letters: 1 point
- 5 letters: 2 points
- 6 letters: 3 points
- 7 letters: 5 points
- 8+ letters: 11 points
Boggle Solver Advanced Features
- Qu Tile Logic: Specialized handling for 'Qu' tiles, treating them as a single grid position as per official game rules.
- JSON Output: Integration-ready results using the --json flag for automated data pipelines.
- Custom Dictionary Support: Users can supplement the built-in lists with their own word files using the --dict flag.
- High-Speed Pruning: Advanced trie-based traversal that handles millions of words with minimal latency within the Openclaw Skills framework.
SKILL.md
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