cyotee/aeon-huggingface-trending
lib/bankr-skills/aeon-huggingface-trending/SKILL.md
Trending Hugging Face models, datasets, and spaces — filtered by license sanity, dedup vs same-week quantizations, with a "why notable" line per pick (architecture shift, size step, license change, notable author). Surfaces what's actually shifting rather than just popular. Triggers: "trending on HF", "what models are hot", "huggingface trending", "new spaces today", "best new datasets".
data-ai
Updated Jul 22, 2026
$ install --global
skillsauthnpx skillsauth add cyotee/indexedex aeon-huggingface-trendingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jul 22, 2026, 3:57 AM214.1s1 file scanned
SKILL.md
- name:
- aeon-huggingface-trending
- description:
- |
- Triggers:
- trending on HF", "what models are hot", "huggingface trending", "new spaces today",
aeon-huggingface-trending
Daily filtered scan over HF's three trending surfaces — models, datasets, spaces — cluster-ranked rather than raw-download ranked.
Endpoints
curl -s "https://huggingface.co/api/models?sort=trending&direction=-1&limit=30"
curl -s "https://huggingface.co/api/datasets?sort=trending&direction=-1&limit=30"
curl -s "https://huggingface.co/api/spaces?sort=trending&direction=-1&limit=30"
Filters
- Empty repos, no commits, no model card → drop.
- Same-week quantization of an already-trending model → demoted to "Quantizations" tail.
- Fork without README delta vs upstream → drop.
- Authors with > 5 trending entries in 24h → demoted (typically aggregators).
- License unclear or missing → flagged inline, not dropped.
"Why notable" line
Per surfaced entry, a one-sentence tag: new architecture / size step / context-window jump / notable author affiliation / license change. If no concrete reason exists, the entry says "no clear why — popular but unremarkable" rather than inventing one.
Output
Three sections — Models, Datasets, Spaces — each with the surviving picks, "why notable", license, and download/view count. Tail section for quantizations.
Rules
- "Why notable" is a hard requirement. No reason → no surface.
- License flags appear inline (Apache 2.0, MIT, OpenRAIL-M, custom-no-commercial). Operators trading on model output care.
- Spaces section often beats Models for builder-tier signal — a working demo is stronger validation than a card claim.
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