Evo Excel Match Analyzer logo

Evo Excel Match Analyzer

Organization
OpenLAIR
evo-excel-match-analyzer

Scores dice games and compares paired matches between players. Loads Excel dice roll data, computes scores using 6 scoring categories (high_and_often, summation, highs_and_lows, only_two_numbers, all_the_numbers, ordered_subset_of_four), finds optimal game scores by pairing different categories across 2 turns, then pairs odd/even games for head-to-head match comparison.

Overview

PublisherOpenLAIR
RepositoryOpenSkill
Skill nameevo-excel-match-analyzer
Stars
97
Forks
4
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by OpenLAIR on GitHub. Read the source before you install it.

Installation

Install the Evo Excel Match Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/OpenLAIR/OpenSkill/tree/main/tasks-evolved/financial-modeling-qa/environment/skills/evo-excel-match-analyzer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/OpenLAIR/OpenSkill.git /tmp/OpenSkill
mkdir -p .claude/skills
cp -r /tmp/OpenSkill/tasks-evolved/financial-modeling-qa/environment/skills/evo-excel-match-analyzer .claude/skills/evo-excel-match-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evo Excel Match Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evo Excel Match Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evo Excel Match Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Excel Match Analyzer

Analyzes dice game data from Excel files. Computes game scores using 6 scoring categories, then pairs odd-numbered games (Player 1) vs even-numbered games (Player 2) for match comparison.

Usage

python
import sys
sys.path.insert(0, '/app/environment/skills/evo-excel-match-analyzer/scripts')
from utils import (
    load_excel_data, compute_all_game_scores, split_by_parity,
    compare_paired_matches, compute_win_difference, write_answer
)

# Load data
data = load_excel_data('/root/data.xlsx', sheet_name='Data')

# Compute all game scores
game_scores = compute_all_game_scores(data)

# Split by parity (odd=P1, even=P2)
p1_scores, p2_scores = split_by_parity(game_scores)

# Compare paired matches (game 1 vs 2, game 3 vs 4, etc.)
p1_wins, p2_wins, ties = compare_paired_matches(p1_scores, p2_scores)

# Compute and write answer
diff = compute_win_difference(p1_wins, p2_wins)
write_answer(diff, '/root/answer.txt')

Scoring Rules (6 Categories)

  1. high_and_often: Highest number × count of that number
  2. summation: Sum of all 6 dice
  3. highs_and_lows: Highest × Lowest × (Highest - Lowest)
  4. only_two_numbers: If exactly 2 distinct numbers → 30 (else N/A)
  5. all_the_numbers: If rolls are {1,2,3,4,5,6} → 40 (else N/A)
  6. ordered_subset_of_four: If rolls contain run of 4 consecutive inc/dec → 50 (else N/A)

Game Scoring

Each game has 2 turns. Find highest combined score using 2 DIFFERENT categories (one per turn). Try all valid category pairs and pick the maximum.

Match Pairing

  • Player 1 plays odd-numbered games (1, 3, 5, ...)
  • Player 2 plays even-numbered games (2, 4, 6, ...)
  • Matches: game 1 vs game 2, game 3 vs game 4, etc.
  • Higher game score wins the match

Key Functions

  • score_high_and_often(rolls) - Category 1 scorer
  • score_summation(rolls) - Category 2 scorer
  • score_highs_and_lows(rolls) - Category 3 scorer
  • score_only_two_numbers(rolls) - Category 4 scorer (returns None if N/A)
  • score_all_the_numbers(rolls) - Category 5 scorer (returns None if N/A)
  • score_ordered_subset_of_four(rolls) - Category 6 scorer (returns None if N/A)
  • compute_turn_scores(rolls) - All applicable scores for a turn
  • compute_game_score(t1_rolls, t2_rolls) - Best combined score for a game
  • load_excel_data(filepath, sheet_name) - Load dice data from Excel
  • compute_all_game_scores(data) - Score all games
  • split_by_parity(game_scores) - Split into P1 (odd) and P2 (even)
  • compare_paired_matches(p1, p2) - Count wins for each player
  • compute_win_difference(p1_wins, p2_wins) - P1 wins minus P2 wins
  • write_answer(result, filepath) - Write numeric result to file

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Evo Excel Match Analyzer AI skill do?

Scores dice games and compares paired matches between players. Loads Excel dice roll data, computes scores using 6 scoring categories (high_and_often, summation, highs_and_lows, only_two_numbers, all_the_numbers, ordered_subset_of_four), finds optimal game scores by pairing different categories across 2 turns, then pairs odd/even games for head-to-head match comparison.

Why use Evo Excel Match Analyzer on TypingMind?

Because you install it once and use it with any model. Evo Excel Match Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evo Excel Match Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenLAIR/OpenSkill/tree/main/tasks-evolved/financial-modeling-qa/environment/skills/evo-excel-match-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evo Excel Match Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evo Excel Match Analyzer?

As many as you like. As long as a model supports skills, you can use Evo Excel Match Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evo Excel Match Analyzer AI skill free?

Yes. It is published on GitHub by OpenLAIR under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇