Dashboard / Repos / League Analyzer

League Analyzer

C 62 completed
Data Tool
web_app / json · small
55
Files
7,720
LOC
3
Frameworks
8
Languages
OverviewFiles & MetricsGit ActivityCall GraphSecurityReports

Pipeline State

completed
Run ID
#353804
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
70.12
Framework unique
—
Isolation
—
Last stage change
2026-05-10 03:35:24
Deduplication group #58798
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Top concepts (1)
Web Frontend
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AI Prompt

I want to build a league analyzer web application. The project should use FastAPI for the backend and React with Vite for the frontend. The goal is to analyze and provide insights on a league or competition. I'll be working with JSON data, and I need the structure to support a web application feel. Please set up the basic scaffolding for this analysis tool.
python fastapi react vite json web-app data-analysis league-analyzer
Generated by gemma4:latest

Catalog Information

The largebubbles__league-analyzer project is designed to analyze and provide insights on a league or competition.

Description

This project appears to be a tool for analyzing data related to a league or competition. It likely provides features such as data visualization, statistics, and possibly even predictions. The target audience seems to be individuals or teams involved in the league or competition, looking to gain a competitive edge through data-driven insights.

الوصف

هذا المشروع يهدف إلى تحليل وتقديم معلومات حول دوري أو منافسة. يحتوي على ميزات مثل الرسوم البيانية، والإحصائيات، وربما حتى التنبؤات. يستهدف هذا المشروع الأفراد أو الفرق المشاركة في الدوري أو المنافسة، الذين يبحثون عن تحسين أداءهم من خلال استغلال المعلومات المستمدة من البيانات.

Novelty

5/10

Tags

league-analysis competition-insights data-visualization statistics predictions

Claude Models

claude-opus-4.6

Quality Score

C
62.1/100
Structure
46
Code Quality
98
Documentation
13
Testing
40
Practices
69
Security
100
Dependencies
60

Strengths

  • Code linting configured (eslint)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • Missing README file \u2014 critical for project understanding
  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 240 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Add a comprehensive README.md explaining purpose, setup, usage, and architecture
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

6.1h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
All rows above produced by Repobility · https://repobility.com
Unknown
License
2.2%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

json
56.7%
python
19.3%
typescript
19.0%
css
3.3%
markdown
1.0%
javascript
0.3%
html
0.3%
text
0.1%

Frameworks

FastAPI React Vite

Concepts (1)

Analysis by Repobility (https://repobility.com) · MCP-ready
CategoryNameDescriptionConfidence
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
auto_categoryWeb Frontendweb-frontend70%

Quality Timeline

1 quality score recorded.

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