musmem-duplicate-contests

Detect duplicate contests by comparing athlete results across six data files.

Updated Mar 1, 2026

Search Tags:#python #data-quality #data-processing #athlete-analysis #bodybuilding #contest-duplicates

One-click install

npx skills add https://github.com/timfogarty1549/musmemSkills --skill musmem-duplicate-contests

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: musmem-duplicate-contests
Source: https://github.com/timfogarty1549/musmemSkills/tree/main/musmem-duplicate-contests
Command: npx skills add https://github.com/timfogarty1549/musmemSkills --skill musmem-duplicate-contests

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps data teams quickly identify instances where the same contest appears under different names across multiple data sources, saving time on manual cross-checks and reconciliation.

Core Features & Use Cases

Cross-file duplicate detection across six data files to surface likely duplicates within the same year.
Two detection strategies: multi-division shows (requires 4+ shared divisions with matching top placements) and single-division shows (top-4 athletes align with some allowances for 5–8 placements).
Generates candidate contest pairs for manual review with year context and guidance for verification.

Quick Start

Run the detection script to identify potential duplicate contests across the six data files and review the candidate pairs.

Frequently Asked Questions about musmem-duplicate-contests

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect duplicate contest entries across multiple data files?▼

You can detect duplicate contest entries by running a Python script that compares athlete results across six data files for each year, surfacing candidate pairs for manual review.

How does duplicate detection handle multi-division and single-division bodybuilding shows?▼

For multi-division shows, detection requires 4+ shared divisions with matching top placements. For single-division shows, it checks if top-4 athletes align with allowances for 5–8 placements.

What data format does the contest duplicate detector expect for parsing?▼

The parser expects lines formatted as Name; Year; Contest; Division-Placement. It ignores placements marked 98 and 0 during the comparison process.

Can I automatically merge duplicate contest records after they are identified?▼

No, the script generates candidate contest pairs for manual review with year context and verification guidance, but does not automatically merge the duplicate records.