paper-daily

name	paper-daily
description	Discover daily arXiv papers for LLM/Agent topics, rank candidates with keyword and institution filters, and prepare a small selected paper list for llm-paper-daily style workflows.

Paper Daily

Use this skill when maintaining a daily LLM/Agent paper list from arXiv.

Workflow

1. Discover candidates from arXiv by priority keywords: Agent, Agents, then LLM.
2. Query target categories such as cs.AI, cs.CL, cs.LG, stat.ML, cs.SE, and cs.MA.
3. Dedupe by normalized arXiv id without version suffix.
4. Filter obvious noise such as chemical/biological/contrast agents.
5. Rank candidates with:
   • keyword priority
   • title/abstract Agent or LLM signals
   • category signals
   • institution signals from QS Top 50 universities and known AI labs/companies
6. Select 3-5 papers for summarization and deterministic README rendering when enough ranked candidates are available; fewer papers are allowed only when filtered candidates are genuinely insufficient.

Commands

Run a real arXiv dry-run for a UTC submitted date:

python3 skill/paper-daily/scripts/discover.py --date YYYY-MM-DD --select 5

Write JSON output:

python3 skill/paper-daily/scripts/discover.py --date YYYY-MM-DD --select 5 --json --out /tmp/papers.json

For local testing with fewer requests:

python3 skill/paper-daily/scripts/discover.py --date YYYY-MM-DD --max-results-per-keyword 10 --select 5

Run the end-to-end local pipeline against the current repo:

python3 skill/paper-daily/scripts/run_daily.py --repo-root . --date YYYY-MM-DD

Manually publish specific arXiv IDs with an explicit display date:

python3 skill/paper-daily/scripts/run_daily.py --repo-root . --date YYYY-MM-DD --arxiv-id 2505.14359v6 --arxiv-id 2512.06746

Inspect a specific date without changing README/feed/state/summary artifacts:

python3 skill/paper-daily/scripts/run_daily.py --repo-root . --date YYYY-MM-DD --view-only

Generate only the canonical/feed outputs:

python3 skill/paper-daily/scripts/generate_feed.py --repo-root . --date YYYY-MM-DD

Notes

• arXiv Atom metadata usually does not include author affiliations. Institution matching in this MVP checks title/abstract and PDF first-page extraction, so it remains a weak signal compared with a dedicated affiliation enricher.
• Keep short aliases conservative. Do not match ambiguous aliases like MIT across the full abstract because words such as committed can create false positives.
• Respect arXiv API etiquette. The CLI defaults to a delay between keyword queries.
• This skill operates on README.md, README_en.md, summary/, and summary_en/.

References

• Institution whitelist: references/institutions.json
• Discovery implementation: scripts/paper_daily/