mlnjsh/ai-research-radar

View on GitHub by @mlnjsh

📡 Self-updating AI research tracker — New papers from arXiv every 6 hours, auto-summarized, trending topics, citation tracking. Powered by GitHub Actions.

What's novel

📡 Self-updating AI research tracker — New papers from arXiv every 6 hours, auto-summarized, trending topics, citation tracking. Powered by GitHub Actions.

Code Analysis

14 files read · 5 rounds

A GitHub Actions-powered pipeline that fetches recent arXiv papers via the Atom API, scores them by keyword relevance, categorizes them into display groups, optionally generates AI summaries, and auto-updates a README with paper tables, trending topics, and weekly digests.

Strengths

Clean, well-organized pipeline with clear separation of concerns across 7 small, focused modules; the stdlib-only core (urllib + xml.etree) keeps dependencies minimal, and the marker-based README update pattern is practical and robust.

Weaknesses

Zero test coverage for any of the 7 source modules, and the core logic is relatively shallow — keyword matching for categorization, first-sentence extraction for summaries, and simple count-based relevance scoring — making it more of a well-structured glue project than a deep implementation.

Score Breakdown

Innovation

4 (25%)

Craft

62 (35%)

Traction

6 (15%)

Scope

63 (25%)

Signal breakdown

Innovation

Not Fork+1

Code Novelty+1

Concept Novelty+1

Craft

Ci+5

Tests+0

Polish+0

Releases+0

Has License+5

Code Quality+18

Readme Quality+15

Recent Activity+7

Structure Quality+5

Commit Consistency+2

Has Dependency Mgmt+5

Traction

Forks+0

Stars+6

Hn Points+0

Watchers+0

Early Traction+0

Devto Reactions+0

Community Contribs+0

Scope

Commits+8

Languages+3

Subsystems+5

Bloat Penalty+0

Completeness+7

Contributors+5

Authored Files+12

Readme Code Match+3

Architecture Depth+5

Implementation Depth+8

Evidence

Commits

Contributors

Files

Active weeks

TestsCI/CDREADMELicenseContributing

Repository

Language

Python

Stars

Forks

License

MIT