Claude Cap

D 58 completed
Api
unknown / python · small
157
Files
46,408
LOC
1
Frameworks
7
Languages

Pipeline State

completed
Run ID
#370787
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
50.00
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48569
Member of a group with 2 similar repo(s) — canonical #93084 view group →
Top concepts (2)
Project DescriptionWeb Backend
Open data scored by Repobility · https://repobility.com

AI Prompt

Create an AI-powered investment analysis pipeline using Python and FastAPI. The system needs to scrape financial data, scan over 2,500 stocks across major indices, and score them using 30+ composite signals. Key features should include surfacing candidates from Finviz screeners and Unusual Whales options flow, assessing portfolio risk, generating conviction-rated Buy/Sell/Hold recommendations, and performing deep research on top picks by analyzing SEC filings and earnings transcripts. The system should also model valuations using DCF and Monte Carlo simulations, all while tracking paper trades with P&L attribution.
python fastapi finance ai stock-analysis api data-scraping investment quantitative web-api
Generated by gemma4:latest

Catalog Information

An AI-driven pipeline that scrapes financial data, analyzes it, and delivers investment insights through a web API.

Description

The system combines web scraping, data processing, and AI analysis to provide actionable investment insights. It retrieves real‑time financial information from public sources, cleans and structures the data with pandas, and visualizes trends using matplotlib. A FastAPI backend exposes endpoints that return processed reports and charts, while a Claude Code agent orchestrates the workflow and generates natural‑language summaries. The pipeline is designed for developers and analysts who need automated, up‑to‑date market intelligence without manual data handling. It reduces the time required to produce investment reports and supports data‑driven decision making. The integration of an AI agent adds contextual understanding and recommendation capabilities beyond simple statistical analysis.

الوصف

يُدمج النظام بين جمع البيانات عبر الإنترنت، معالجة البيانات، وتحليل الذكاء الاصطناعي لتقديم رؤى استثمارية قابلة للتنفيذ. يقوم بجمع المعلومات المالية اللحظية من المصادر العامة، ثم ينظف ويهيئ البيانات باستخدام مكتبة pandas، ويُظهر الاتجاهات عبر رسومات matplotlib. تُعرّف واجهة FastAPI نقاط نهاية تُعيد تقارير ومعالجات مرئية، بينما يُنسق وكيل Claude Code سير العمل ويُنتج ملخصات بلغة طبيعية. صُمم هذا الأنابيب للمطورين والمحللين الذين يحتاجون إلى معلومات سوقية مُحدثة تلقائياً دون تدخل يدوي. يقلل من الوقت اللازم لإعداد تقارير الاستثمار ويُعزز اتخاذ القرارات المبنية على البيانات. يميز المشروع بدمج وكيل ذكاء اصطناعي يضيف فهمًا سياقيًا وتوصيات تتجاوز التحليل الإحصائي البسيط.

Novelty

7/10

Tags

investment-analysis ai-driven-insights financial-data-scraping visual-analytics automated-reporting portfolio-evaluation market-trend-analysis

Technologies

beautifulsoup fastapi matplotlib pandas uvicorn

Claude Models

claude (unknown version) claude-opus-4.6

Quality Score

D
58.0/100
Structure
64
Code Quality
61
Documentation
73
Testing
50
Practices
42
Security
54
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Properly licensed project

Weaknesses

  • No CI/CD configuration \u2014 manual testing and deployment
  • Potential hardcoded secrets in 1 files
  • 3101 duplicate lines detected \u2014 consider DRY refactoring
  • 10 'god files' with >500 LOC need decomposition

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Move hardcoded secrets to environment variables or a secrets manager
  • Address 78 TODO/FIXME items \u2014 consider tracking them as issues

Security & Health

36.1h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility · open methodology · https://repobility.com/research/
MIT
License
5.4%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
56.6%
json
34.5%
markdown
5.9%
shell
1.6%
javascript
1.2%
toml
0.1%
text
0.0%

Frameworks

FastAPI

Concepts (2)

Repobility · the analyzer behind every row · https://repobility.com
CategoryNameDescriptionConfidence
Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data.
auto_descriptionProject DescriptionAI-powered investment analysis pipeline that scans 2,500 stocks, scores them with 30+ composite signals, assesses portfolio risk, generates conviction-rated trade recommendations, and runs deep research — all orchestrated by Claude Code agent teams.80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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