Excel Match Analyzer
SkillFiles & storageScores 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Excel Match Analyzer skill
What this skill tells your AI
The instructions your AI receives, as published by openlair/openskill in tasks-evolved/financial-modeling-qa/environment/skills/evo-excel-match-analyzer/SKILL.md and read by ahel’s review.
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
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)
- high_and_often: Highest number × count of that number
- summation: Sum of all 6 dice
- highs_and_lows: Highest × Lowest × (Highest - Lowest)
- only_two_numbers: If exactly 2 distinct numbers → 30 (else N/A)
- all_the_numbers: If rolls are {1,2,3,4,5,6} → 40 (else N/A)
- 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 scorerscore_summation(rolls)- Category 2 scorerscore_highs_and_lows(rolls)- Category 3 scorerscore_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 turncompute_game_score(t1_rolls, t2_rolls)- Best combined score for a gameload_excel_data(filepath, sheet_name)- Load dice data from Excelcompute_all_game_scores(data)- Score all gamessplit_by_parity(game_scores)- Split into P1 (odd) and P2 (even)compare_paired_matches(p1, p2)- Count wins for each playercompute_win_difference(p1_wins, p2_wins)- P1 wins minus P2 winswrite_answer(result, filepath)- Write numeric result to file
Signals
- GitHub stars
- 89
- Forks
- 4
- Last commit
- Sep 2026
Advanced
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- skill
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evo-excel-match-analyzer- Source
- github.com/openlair/openskill