What belongs on the radar
Tools, GitHub repos, models, papers, frameworks, packages, agents, MCP servers, local AI utilities, and practical AI projects. Company news, funding, partnerships, and policy changes live on /news/.
Trust model
Methodology
RepoRadar is an evidence-linked AI discovery radar. It ranks useful AI tools, repos, models, papers, frameworks, releases, and practical AI projects while keeping popularity, evidence, risk, and editorial verdicts visible and separate.
How items are found
Source-backed public channels: GitHub, Hugging Face, arXiv, Hacker News, PyPI, official blogs, changelogs, package pages, model cards, papers, and docs. Source defaults include cadence and freshness expectations.
Scoring firewalls
Sponsors cannot buy organic ranking, score changes, risk-label changes, verdict changes, or removal of criticism. Tips, ads, and newsletter growth never influence score, tier, rank, or visibility.
Risk and caution
Risk means inherent user-impacting hazard, not novelty. Caution flags cover not hands-on tested, setup difficulty, unclear pricing, weak docs, new or experimental, weak AI relevance, and manual review needed.
Current scoring formula
The public score follows the current implementation in radar_pipeline/public_site.py: usefulness 35%, novelty 18%, momentum 14%, maturity 10%, open-source/build quality 7%, evidence 6%, commercial/workflow potential 6%, setup ease 4%. Popularity is tracked separately from usefulness. Sponsored status, newsletter growth, tips, ads, and support links never affect score, tier, rank, risk, caution, verdict, audience, difficulty, or popularity.
Tier calibration
- Gold score ≥ 7.5 when eligible, or top eligible signal with score ≥ 7.0
- Silver score ≥ 6.5 and useful enough to browse
- Bronze useful, niche, early, or watchlist-worthy signals
- Low Signal weak, noisy, low-transparency, low-value, or weak-AI-relevance items
Gold eligibility gates
Gold requires medium or high confidence, usable/official/cross-verified evidence or better, clear public descriptions, no excluded category, no weak or unclear AI relevance, and no fallback, triage-only, weak-evidence, low-signal, or low-transparency flags.
Evidence levels
- Mentionedseen in a community, social, or directory source
- Officialsupported by official docs, changelog, model card, paper, package page, or company post
- Usablehas a usable demo, package, API, code, model, or dataset
- Verified / Testedclaims were checked more deeply or a hands-on test was actually performed and logged
What gets flagged as risk
RepoRadar flags sensitive data access, local file or document access, browser or session or cookie access, OAuth or workspace or account access, email or calendar or message sending, shell or terminal or code execution, deployment or external-system modification, autonomous action, regulated-domain claims, provenance or watermark removal, scraping or surveillance or deepfake or voice cloning or NSFW or cheating surfaces, and unknown binaries or admin installs.
Caution labels are separate from risk. They cover not hands-on tested, setup difficulty, unclear pricing, weak docs, new or experimental, weak AI relevance, and manual review needed.
Source health and review queues
The pipeline tracks operational health fields such as items seen, accepted, held back or dead-lettered, source failures, rate limits, zero-item anomalies, and review queues. Those health signals are for trust and debugging; they do not create paid placement or automatic boosts.
Editorial independence
Sponsors cannot buy organic ranking, score changes, risk-label changes, verdict changes, or removal of criticism. Financial support does not buy ranking, coverage, score changes, risk-label changes, verdict changes, visibility, popularity, or editorial treatment.