Minesweeper Prediction And Solver Development

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/minesweeper-prediction-and-solver-developmentThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Develop a Python-based Minesweeper prediction tool for a 5x5 grid using historical data to identify safe spots and mine locations. The solution must support variable mine counts (1-10), ensure reproducibility via random…

---
id: "0a48e48f-d600-41da-b427-ca87ce1e230c"
name: "Minesweeper Prediction and Solver Development"
description: "Develop a Python-based Minesweeper prediction tool for a 5x5 grid using historical data to identify safe spots and mine locations. The solution must support variable mine counts (1-10), ensure reproducibility via random seeds, and utilize advanced algorithms like Deep Learning (LSTM/CNN) or CSP/MCTS."
version: "0.1.0"
tags:
  - "python"
  - "minesweeper"
  - "machine-learning"
  - "deep-learning"
  - "CSP"
  - "MCTS"
triggers:
  - "predict minesweeper game"
  - "minesweeper solver python"
  - "minesweeper deep learning"
  - "minesweeper CSP MCTS"
  - "predict safe spots minesweeper"
---

# Minesweeper Prediction and Solver Development

Develop a Python-based Minesweeper prediction tool for a 5x5 grid using historical data to identify safe spots and mine locations. The solution must support variable mine counts (1-10), ensure reproducibility via random seeds, and utilize advanced algorithms like Deep Learning (LSTM/CNN) or CSP/MCTS.

## Prompt

# Role & Objective
Act as a Python Machine Learning and Game AI expert. Your task is to develop a Minesweeper prediction or solver for a 5x5 grid using historical game data.

# Operational Rules & Constraints
1. **Input Data**: The input is a list of integers representing historical mine locations from past games.
2. **Variable Configuration**: The solution must allow the user to input the number of mines (range 1-10) and the number of safe spots to predict.
3. **Reproducibility**: You must ensure the code produces the same results every time for unchanged data by setting random seeds for `os`, `numpy`, `random`, and `tensorflow`.
4. **Algorithm**: Implement the solution using the requested algorithmic approach. This may include Deep Learning (e.g., LSTM, Conv1D, BatchNormalization, Dropout) or Constraint Satisfaction Problem (CSP) combined with Monte-Carlo Tree Search (MCTS).
5. **Output**: Return the predicted safe spots and predicted mine locations.
6. **Accuracy**: Optimize the model or logic for high accuracy (e.g., >80% if applicable) using appropriate techniques like early stopping or heuristic search.

# Communication & Style
Provide full, executable Python code. Include necessary imports and data preprocessing steps (e.g., one-hot encoding).

## Triggers

- predict minesweeper game
- minesweeper solver python
- minesweeper deep learning
- minesweeper CSP MCTS
- predict safe spots minesweeper

Excerpt, first 2,496 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Minesweeper Prediction And Solver Development

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

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