TopRank Skills

Official OpenClaw rules 36%

boggle

Solve Boggle boards — find all valid words (German + English) on a 4x4 letter grid. Use when the user shares a Boggle photo, asks for words on a grid, or plays word games. Includes 1.7M word dictionaries (DE+EN).

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Status

ACTIVE

Visibility

PUBLIC

安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 boggle 技能。 若已安装,则直接安装 boggle 技能。

Overview

Skill Key
christianhaberl/boggle
Author
christianhaberl
Source Repo
openclaw/skills
Version
-
Source Path
skills/christianhaberl/boggle
Latest Commit SHA
baf44279fb4f51f655c643bc7c72599e34ddc8c7

Extracted Content

SKILL.md excerpt

# Boggle Solver

Fast trie-based DFS solver with dictionary-only matching. No AI/LLM guessing — words are validated exclusively against bundled dictionaries (359K English + 1.35M German).

## Workflow (from photo)

1. **Read the 4x4 grid** from the photo (left-to-right, top-to-bottom)
2. **Show the grid to the user and ask for confirmation** before solving
3. Only after user confirms → run the solver
4. **Always run English and German SEPARATELY** — present as two labeled sections (🇬🇧 / 🇩🇪)

## Solve a board

```bash
# English
python3 skills/boggle/scripts/solve.py ELMU ZBTS ETVO CKNA --lang en

# German
python3 skills/boggle/scripts/solve.py ELMU ZBTS ETVO CKNA --lang de
```

Each row is one argument (4 letters). Or use `--letters`:
```bash
python3 skills/boggle/scripts/solve.py --letters ELMUZBTSETVOCKNA --lang en
```

## Options

| Flag | Description |
|---|---|
| `--lang en/de` | Language (default: en; **always run EN and DE separately**) |
| `--min N` | Minimum word length (default: 3) |
| `--json` | JSON output with scores |
| `--dict FILE` | Custom dictionary (repeatable) |

## Scoring (standard Boggle)

- 3-4 letters: 1 pt
- 5 letters: 2 pts
- 6 letters: 3 pts
- 7 letters: 5 pts
- 8+ letters: 11 pts

## How it works

- Builds a trie from dictionary files (one-time, ~11s)
- DFS traversal from every cell, pruned by trie prefixes
- Adjacency: 8 neighbors (horizontal, vertical, diagonal)
- Each cell used at most once per word
- **Qu tile support:** Standard Boggle "Qu" tiles are handled as a single cell (e.g., `QUENHARI...` → "QU" occupies one position)
- **All matching is dictionary-only** — no generative/guessed words

## Data

Dictionaries are auto-downloaded from GitHub on first run if missing.


- `data/words_english_boggle.txt` — 359K English words
- `data/words_german_boggle.txt` — 1.35M German words

## Performance

- Trie build: ~11s (first run, 1.7M words)
- Solve: <5ms per board

README excerpt

# 🎲 Boggle Solver — OpenClaw Skill

Fast trie-based DFS Boggle solver for [OpenClaw](https://github.com/openclaw/openclaw).

## Features

- **1.7M dictionary words** — 359K English + 1.35M German
- **Qu-tile support** — standard Boggle rules
- **< 5ms solve time** per board
- **JSON output** with Boggle scoring
- **Bilingual** — run English and German separately

## Install

```bash
clawdhub install boggle
```

Or manually copy the `skills/boggle/` folder into your OpenClaw workspace.

## Usage

```bash
# English
python3 scripts/solve.py ELMU ZBTS ETVO CKNA --lang en

# German
python3 scripts/solve.py ELMU ZBTS ETVO CKNA --lang de

# With --letters flag
python3 scripts/solve.py --letters ELMUZBTSETVOCKNA --lang en

# JSON output
python3 scripts/solve.py ELMU ZBTS ETVO CKNA --lang en --json
```

## Options

| Flag | Description |
|---|---|
| `--lang en/de` | Dictionary language (default: en) |
| `--min N` | Minimum word length (default: 3) |
| `--json` | JSON output with scores |
| `--dict FILE` | Custom dictionary (repeatable) |

## Scoring (standard Boggle)

- 3-4 letters: 1 pt
- 5 letters: 2 pts
- 6 letters: 3 pts
- 7 letters: 5 pts
- 8+ letters: 11 pts

## How it works

- Builds a trie from dictionary files
- DFS traversal from every cell, pruned by trie prefixes
- Adjacency: 8 neighbors (horizontal, vertical, diagonal)
- Each cell used at most once per word
- Qu tiles handled as single cell
- **All matching is dictionary-only** — no AI guessing

## AI-Reviewed

This skill was reviewed by **Codex** and **Gemini Code Assist** across 5 review rounds. All findings addressed.

## License

MIT

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