Ai Strategy

D 57 completed
Cli Tool
unknown / python · tiny
32
Files
1,851
LOC
1
Frameworks
5
Languages

Pipeline State

completed
Run ID
#361687
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
32.84
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48057
Member of a group with 1 similar repo(s) — canonical #6835 view group →
Top concepts (2)
Project DescriptionTesting
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/

AI Prompt

Create a command-line interface (CLI) tool in Python for AI market intelligence. I need it to scrape data from sources like GitHub Trending, GitHub Releases, and ArXiv. The system should automatically collect, score, and generate a daily digest. Key features include scoring items based on stack match (e.g., Python +10), role match, source quality, keywords, and engagement. It must support searching collected data using a query and optionally filtering by domain like 'code' or 'research'. Finally, it should allow viewing the latest digest or a digest for a specific date.
python cli ai market-intelligence scraping data-analysis github arxiv command-line
Generated by gemma4:latest

Catalog Information

An AI‑driven market intelligence CLI that scrapes industry data, analyzes trends, and builds a knowledge base for strategic decision‑making.

Description

The system continuously monitors AI industry sources, extracting relevant information through web scraping. It processes the collected data to identify emerging trends and converts them into actionable tool recommendations. A structured knowledge base is maintained, enabling users to query historical insights and forecast future developments. Designed for AI researchers, product managers, and business analysts, it helps teams stay ahead of market shifts. The tool’s terminal interface, powered by a rich UI, offers real‑time dashboards and customizable alerts. By automating data collection and analysis, it reduces manual research effort and supports evidence‑based strategy planning.

الوصف

تقوم هذه الأداة بمراقبة مستمرة لمصادر صناعة الذكاء الاصطناعي، وتستخرج المعلومات ذات الصلة عبر تقنية استخراج البيانات من الويب. تُعالج البيانات المجمعة لتحديد الاتجاهات الناشئة وتحويلها إلى توصيات عملية للأدوات التي يمكن اعتمادها. تُبنى قاعدة معرفية منظمة تسمح للمستخدمين بالاستعلام عن الرؤى التاريخية وتوقع التطورات المستقبلية. تستهدف الباحثين في الذكاء الاصطناعي ومديري المنتجات والمحللين التجاريين، وتساعدهم على البقاء في صدارة تحولات السوق. واجهة سطر الأوامر، المدعومة بواجهة رسومية غنية، توفر لوحات معلومات فورية وتنبيهات قابلة للتخصيص. من خلال أتمتة جمع البيانات وتحليلها، تقلل الأداة الجهد اليدوي في البحث وتدعم اتخاذ القرارات الاستراتيجية المبنية على الأدلة.

Novelty

7/10

Tags

market-intelligence trend-analysis web-scraping knowledge-base ai-industry-monitoring data-aggregation pipeline-automation

Technologies

beautifulsoup rich

Claude Models

claude-opus-4.6

Quality Score

D
56.6/100
Structure
56
Code Quality
71
Documentation
67
Testing
0
Practices
61
Security
82
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

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
  • Potential hardcoded secrets in 1 files

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)
  • Move hardcoded secrets to environment variables or a secrets manager

Security & Health

5.1h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (7)
Source: Repobility analyzer · https://repobility.com
Unknown
License
1.3%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
46.1%
markdown
42.4%
yaml
10.5%
toml
0.8%
shell
0.3%

Frameworks

pytest

Concepts (2)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
About: code-quality intelligence by Repobility · https://repobility.com
auto_descriptionProject DescriptionAI market intelligence system: automated collection, scoring, and search of AI/ML news and trends.80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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