Synthszr

D 55 completed
Web App
web_app / typescript · small
485
Files
73,406
LOC
3
Frameworks
8
Languages

Pipeline State

completed
Run ID
#358643
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
49.67
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47441
Member of a group with 4 similar repo(s) — canonical #1452817 view group →
Top concepts (2)
Project DescriptionWeb Frontend
About: code-quality intelligence by Repobility · https://repobility.com

AI Prompt

Create an AI-powered newsletter aggregator web application. I need the frontend built with React and Next.js, and I want to use TypeScript for development. The system must integrate with AI services like Anthropic, Google Generative AI, or OpenAI to aggregate content. It needs a backend structure capable of handling API routes, managing user authentication via Supabase, and supporting admin functionalities. Please ensure the setup includes environment variable management for secrets like API keys, and consider implementing cron jobs for scheduled tasks.
typescript react next.js ai newsletter web-app supabase api aggregation
Generated by gemma4:latest

Catalog Information

AI-powered newsletter aggregator for individuals and organizations.

Description

Synthszr is an AI-driven newsletter aggregation platform that offers a unique twist on traditional news feed management. It allows users to create custom newsletters by aggregating content from various sources, including articles, blogs, and social media platforms. The platform uses machine learning algorithms to analyze user behavior and preferences, providing personalized recommendations for relevant content. Synthszr also includes features such as email marketing automation, analytics, and customizable templates.

الوصف

هو نظام جمع وتحليل الأخبار باستخدام الذكاء الاصطناعي، يتيح للمستخدمين إنشاء إشعارات شخصية من خلال تجميع المحتوى من مصادر متعددة، بما في ذلك المقالات والمدونات ومجتمعات التواصل الاجتماعي. يستخدم النظام خوارزميات التعلم الآلي لتحليل سلوك المستخدم وتوقعاته، مما يتيح توصيات محددة للمحتوى المهم. كما يحتوي على ميزات مثل تلقيم البريد الإلكتروني والتحليلات وتماثيل قابلة للتخصيص.

Novelty

7/10

Tags

newsletter-aggregation ai-powered content-recommendation email-marketing-automation analytics customizable-templates

Technologies

anthropic framer-motion nextjs openai radix-ui react recharts supabase tailwind vitest zod

Claude Models

claude-sonnet-4.6

Quality Score

D
54.8/100
Structure
56
Code Quality
57
Documentation
52
Testing
55
Practices
52
Security
55
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Properly licensed project

Weaknesses

  • 3 files with critical complexity need refactoring
  • Potential hardcoded secrets in 2 files
  • 10261 duplicate lines detected \u2014 consider DRY refactoring
  • 20 'god files' with >500 LOC need decomposition

Recommendations

  • Add a linter configuration to enforce code style consistency
  • Move hardcoded secrets to environment variables or a secrets manager
  • Address 40 TODO/FIXME items \u2014 consider tracking them as issues

Security & Health

44.1h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
All rows above produced by Repobility · https://repobility.com
MIT
License
12.8%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

typescript
86.9%
yaml
6.9%
sql
3.2%
javascript
1.7%
css
0.5%
markdown
0.5%
json
0.3%
html
0.0%

Frameworks

React Next.js Vitest

Concepts (2)

Findings produced by Repobility · scan your repo at https://repobility.com/scan/
CategoryNameDescriptionConfidence
Same scanner, your repo: https://repobility.com — Repobility
auto_descriptionProject Description![Security Scan](https://github.com/mattesmattes/synthszr/actions/workflows/security.yml) ![License: MIT](https://opensource.org/licenses/MIT)80%
auto_categoryWeb Frontendweb-frontend70%

Quality Timeline

1 quality score recorded.

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