Pitlane Ai

C+ 78 completed
Ai Ml
monorepo / python · small
186
Files
30,127
LOC
1
Frameworks
8
Languages

Pipeline State

completed
Run ID
#305743
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
60.07
Framework unique
Isolation
Last stage change
2026-05-10 03:34:57
Deduplication group #51398
Member of a group with 9 similar repo(s) — canonical #2124 view group →
Top concepts (12)
Project DescriptionTestingFactoryStrategyCachingConfigurationFile ManagementLoggingSearchTestingUser ManagementAuthentication
Source: Repobility analyzer · https://repobility.com

AI Prompt

Create an AI-powered application for Formula 1 data analysis. I need it to analyze lap times, visualize tyre strategies, and process race telemetry data. The system should also allow querying driver information from 1950 onwards and browsing complete event schedules. Since it uses an AI agent backbone, please ensure the structure supports demonstrating agent capabilities, perhaps using a web interface that can be run in development mode.
python ai f1 data-analysis agent-sdk web-app pytest
Generated by gemma4:latest

Catalog Information

This project provides F1 data analysis capabilities using artificial intelligence.

Description

Pitlane-AI is a platform that leverages the power of AI to analyze and provide insights from Formula 1 data. It utilizes machine learning algorithms to extract meaningful information, enabling users to gain a deeper understanding of the sport. The project aims to improve the fan experience by offering data-driven analysis and predictions.

الوصف

يستخدم Pitlane-AI قوة الذكاء الاصطناعي لتحليل وتقديم معلومات حول البيانات من سباقات فورمولا 1. يستخدم هذا المشروع خوارزميات التعلم الآلي لاستخراج المعلومات المهمة، مما يسمح للمستخدمين بالفهم الأعمق للرياضة. يهدف المشروع إلى تحسين تجربة المشجعين عن طريق تقديم التحليلات والتنبؤات المستندة على البيانات.

Novelty

7/10

Tags

formula-one data-analysis artificial-intelligence machine-learning sports-analytics

Claude Models

claude-sonnet-4.6

Quality Score

C+
77.8/100
Structure
88
Code Quality
64
Documentation
85
Testing
85
Practices
70
Security
84
Dependencies
90

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (100% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • 1532 duplicate lines detected \u2014 consider DRY refactoring
  • 1 'god files' with >500 LOC need decomposition

Security & Health

6.3h
Tech Debt (A)
Medium
DORA Rating
A
OWASP (100%)
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PASS
Quality Gate
A
Risk (0)
Apache-2.0
License
9.9%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
71.6%
markdown
22.8%
html
2.4%
yaml
2.1%
toml
0.8%
css
0.1%
shell
0.0%
javascript
0.0%

Frameworks

pytest

Symbols

function191
variable172
constant101
method38
class28
property2

API Endpoints (8)

Same analyzer free for public repos: https://repobility.com
MethodPathHandlerFramework
Repobility · code-quality intelligence · https://repobility.com
GET/indexFastAPI/Flask
POST/api/chatchatFastAPI/Flask
GET/api/conversationslist_conversationsFastAPI/Flask
GET/api/conversations/{conversation_id}/messagesget_conversation_messagesFastAPI/Flask
POST/api/conversations/{conversation_id}/resumeresume_conversationFastAPI/Flask
POST/api/conversations/newnew_conversationFastAPI/Flask
GET/charts/{session_id}/{filename}serve_chartFastAPI/Flask
GET/healthhealthFastAPI/Flask

Concepts (13)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
Repobility · code-quality intelligence platform · https://repobility.com
auto_descriptionProject DescriptionAI-powered Formula 1 data analysis - from lap times and tyre strategy to race telemetry and historical insights. Built with Claude's Agent SDK to demonstrate practical applications of AI agents in domain-specific analysis. This project explores the intersection of motorsport data and modern agent ar80%
auto_categoryTestingtesting70%
design_patternFactoryFound factory/create_ naming patterns60%
design_patternStrategyFound strategy/policy-named files60%
business_logicCachingDetected from 3 related files50%
business_logicConfigurationDetected from 5 related files50%
business_logicFile ManagementDetected from 2 related files50%
business_logicLoggingDetected from 2 related files50%
business_logicSearchDetected from 4 related files50%
business_logicTestingDetected from 59 related files50%
business_logicUser ManagementDetected from 5 related files50%
business_logicAuthenticationDetected from 6 related files50%
business_logicAnalyticsDetected from 2 related files50%
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Quality Timeline

1 quality score recorded.

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