Sportradar Demo
F 49 completed
Other
monorepo / json · small
116
Files
25,980
LOC
4
Frameworks
10
Languages
Pipeline State
completedRun ID
#394615Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
67.60Framework unique
—Isolation
—Last stage change
2026-05-10 03:35:34Deduplication group #52780
Member of a group with 2 similar repo(s) — this repo is canonical view group →
Top concepts (2)
Project DescriptionWeb Frontend
Repobility — the code-quality scanner for AI-generated software · https://repobility.com
AI Prompt
Create an agentic web application for NBA analytics called SportScout AI. The app should accept natural-language goals about NBA basketball. It needs to show a visible execution plan before running any tools. The system must support five server-side tools: one for querying players using pandas, one to fetch data from the Sportradar NBA API, one for comparing multiple entities and generating charts, one for searching session history using SQLite FTS5, and one to generate an Excel export. Additionally, it must support client-side actions like rendering various types of charts, displaying data tables, triggering file downloads, and showing toast notifications. The frontend should use React and Tailwind CSS, and the backend should utilize FastAPI.
python react fastapi tailwindcss agentic nba analytics web-app json typescript
Generated by gemma4:latest
Catalog Information
An agentic web application that accepts natural-language goals about NBA basketball, produces a visible execution plan, and completes tasks using both server-side tools and client-side actions.
Description
An agentic web application that accepts natural-language goals about NBA basketball, produces a visible execution plan, and completes tasks using both server-side tools and client-side actions.
Novelty
3/10Tags
python react fastapi tailwindcss agentic nba analytics web-app json typescript
Claude Models
claude-opus-4-6
Quality Score
F
49.4/100
Structure
41
Code Quality
53
Documentation
50
Testing
0
Practices
74
Security
92
Dependencies
60
Strengths
- Code linting configured (eslint, ruff (possible))
- Good security practices \u2014 no major issues detected
- Containerized deployment (Docker)
Weaknesses
- No LICENSE file \u2014 legal ambiguity for contributors
- No tests found \u2014 high risk of regressions
- No CI/CD configuration \u2014 manual testing and deployment
- 4 files with critical complexity need refactoring
- 1536 duplicate lines detected \u2014 consider DRY refactoring
- 6 'god files' with >500 LOC need decomposition
Recommendations
- Add a test suite \u2014 start with critical path integration tests
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Add a LICENSE file (MIT recommended for open source)
Security & Health
13.3h
Tech Debt (B)
A
OWASP (100%)
FAIL
Quality Gate
A
Risk (13)
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/
Unknown
License
3.4%
Duplication
Languages
Frameworks
FastAPI React Tailwind CSS Vite
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Repobility · code-quality intelligence · https://repobility.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | An agentic web application that accepts natural-language goals about NBA basketball, produces a visible execution plan, and completes tasks using both server-side tools and client-side actions. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Web Frontend | web-frontend | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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