Best Day Trainer
D 57 completed
Other
web_app / json · small
74
Files
18,965
LOC
3
Frameworks
6
Languages
Pipeline State
completedRun ID
#387774Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
46.80Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47255
Member of a group with 1 similar repo(s) — canonical #103068 view group →
Top concepts (2)
Project DescriptionWeb Frontend
Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot
AI Prompt
Create a full-stack web application for personal trainers to analyze and document training sessions. The app needs to allow users to record or upload videos (MP4, WebM, MOV) using a chunked upload system with retries. After upload, it must use AI, specifically Google Gemini, to identify exercises and analyze form, and then use Claude to generate professional session notes, including observations and recommendations. Key features include building a searchable exercise library with filters (strength, cardio, etc.), tracking session status, and providing a responsive UI with dark/light themes. The tech stack should utilize Next.js 16, React, TypeScript, Drizzle ORM with SQLite, and Tailwind CSS.
next.js react typescript full-stack ai video-analysis drizzle sqlite fitness web-app
Generated by gemma4:latest
Catalog Information
A full-stack web application that helps personal trainers record, analyze, and document training sessions using AI. Upload or record a session video, and the app automatically identifies each exercise, extracts clips, analyzes form, generates coaching notes, and builds a searchable exercise library.
Description
A full-stack web application that helps personal trainers record, analyze, and document training sessions using AI. Upload or record a session video, and the app automatically identifies each exercise, extracts clips, analyzes form, generates coaching notes, and builds a searchable exercise library.
Novelty
3/10Tags
next.js react typescript full-stack ai video-analysis drizzle sqlite fitness web-app
Technologies
anthropic drizzle nextjs react tailwind zod
Claude Models
claude-opus-4-6
Quality Score
D
57.1/100
Structure
51
Code Quality
96
Documentation
36
Testing
0
Practices
60
Security
84
Dependencies
60
Strengths
- Code linting configured (eslint)
- 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
- 2 files with critical complexity need refactoring
- 535 duplicate lines detected \u2014 consider DRY refactoring
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
12.8h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Same scanner, your repo: https://repobility.com — Repobility
Unknown
License
3.5%
Duplication
Languages
Frameworks
React Next.js Drizzle
Concepts (2)
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| auto_description | Project Description | A full-stack web application that helps personal trainers record, analyze, and document training sessions using AI. Upload or record a session video, and the app automatically identifies each exercise, extracts clips, analyzes form, generates coaching notes, and builds a searchable exercise library. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Web Frontend | web-frontend | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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