aeon-paper-pick
Skill17 starsChanged 5 months agoMITView on GitHub
Surface the one AI / ML paper to read today from Hugging Face Papers, with the central claim, why it's worth an hour, where it might be wrong, and a time-budgeted read order. Filters out pure benchmark-chasing and incremental scaling reports. Use as a daily morning brief input for AI-savvy operators. Triggers: "one paper to read today", "best AI paper today", "what's the must-read paper", "HF Papers top pick".
2 other projects use a version of this.
Adopted by
Most recently taken up by
- BankrBot/openclaw-skillsword for word, first seen Oct 8, 2026
- BankrBot/skillsword for word, first seen Apr 28, 2026
Other versions2 projects use a version of this.
Word for word · 2
- BankrBot/openclaw-skills★ 1.2k100% same
- BankrBot/skills★ 1.2k100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository84 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/AGENTS.mdAGENTS.md
- .cursor/rules/codegraph.mdcCursor rule
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 50
If 0 papers survive the filter:
- Distinctive: line 63
Read order time-budgeted. Save the reader from skimming the whole PDF.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
aeon-paper-pick
One paper per day. Not a digest — one pick, with a short brief that lets the reader decide whether to invest the next hour.
How the pick works
- Fetch last 24h of HF Papers (
https://huggingface.co/papers). - Drop pure benchmark-chasing (new SOTA on existing leaderboard, no method change), incremental scaling reports, and position papers without empirical claims.
- Score survivors on novelty of method/framing, falsifiability of central claim, reproducibility signal (code + weights + data), and cross-discipline applicability.
- Pick the highest scoring. Tie-break: sharper falsifiable claim.
Brief format
[Paper title]
Authors: A, B, C (Lab)
arXiv: 2505.xxxxx
Central claim: [one sentence, plain English]
Why it's worth an hour:
- [method shift, not benchmark bump — they replace X with Y]
- [claim is falsifiable: ablation in §4 isolates X vs not-X cleanly]
- [code + weights released, reproducible at home]
Where it might be wrong:
- [training distribution is narrow — open question whether the effect transfers]
- [comparison baseline is older than expected]
Read order:
1. §3 (method) — 8 min
2. §4 (ablations) — 12 min
3. §6 (limitations) — 5 min
Optional: §5 (extended experiments)Empty days
If 0 papers survive the filter:
No surviving picks today. 14 papers filtered out: 6 benchmark-chasing, 5 incremental scaling, 3 position papers.
Worth scrolling yourself: huggingface.co/papersHonesty over manufactured picks.
Rules
- One pick, not three. Three picks is a digest, and digests become wallpaper.
- "Where it might be wrong" is mandatory.
- Read order time-budgeted. Save the reader from skimming the whole PDF.
- Cite actual sections so the reader can verify the brief.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

