Assist

C+ 74 completed
Other
web_app / json · small
73
Files
15,498
LOC
5
Frameworks
10
Languages

Pipeline State

completed
Run ID
#397014
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
57.87
Framework unique
Isolation
Last stage change
2026-05-10 03:35:17
Deduplication group #53273
Member of a group with 4 similar repo(s) — canonical #101757 view group →
Top concepts (2)
Project DescriptionWeb Frontend
About: code-quality intelligence by Repobility · https://repobility.com

AI Prompt

Create an AI-powered basketball training partner application called 'Assist'. I need it to function as a personalized skill trainer and a weekly planning tool. For the skill lab, it should generate 'Daily Routine Cards' by selecting specific drills from a vector database, structuring them into a warm-up, main drills, and cool-down checklist based on a user's weaknesses. For the weekly plan, I need a feature that generates 'Weekly Training Plans' spanning 1-7 days using a LangGraph agent that diagnoses needs, plans the week, retrieves drills, and generates custom variations if necessary. Additionally, include a 'Gear Advisor' that recommends basketball shoes based on subjective 'Sensory Preferences' and 'Player Archetypes'. The stack should utilize FastAPI for the backend and React/Next.js for the frontend.
python fastapi react next.js langgraph ai basketball fitness web-app rag
Generated by gemma4:latest

Catalog Information

🌐 Live Demo: https://assist-frontend-plum.vercel.app

Description

🌐 Live Demo: https://assist-frontend-plum.vercel.app

Novelty

3/10

Tags

python fastapi react next.js langgraph ai basketball fitness web-app rag

Technologies

fastapi langchain openai pydantic

Claude Models

claude-opus-4-6

Quality Score

C+
74.4/100
Structure
78
Code Quality
82
Documentation
59
Testing
55
Practices
80
Security
92
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • 367 duplicate lines detected \u2014 consider DRY refactoring

Security & Health

6.6h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
Repobility — the code-quality scanner for AI-generated software · https://repobility.com
MIT
License
4.2%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

json
65.9%
python
23.8%
markdown
6.4%
typescript
3.2%
toml
0.2%
yaml
0.2%
xml
0.2%
javascript
0.0%
text
0.0%
css
0.0%

Frameworks

FastAPI React Next.js pytest Tailwind CSS

Concepts (2)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
auto_descriptionProject Description<b>Assist</b> is an intelligent agent project that combines 'LangGraph' and 'RAG' technologies to help <b>hoopers</b> enhance their performance through data-driven insights.80%
auto_categoryWeb Frontendweb-frontend70%

Quality Timeline

1 quality score recorded.

View File Metrics

Embed Badge

Add to your README:

![Quality](https://repos.aljefra.com/badge/121378.svg)
Quality BadgeSecurity Badge
Export Quality CSVDownload SBOMExport Findings CSV