| 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
- Discover candidates from arXiv by priority keywords:
Agent, Agents, then LLM.
- Query target categories such as
cs.AI, cs.CL, cs.LG, stat.ML, cs.SE, and cs.MA.
- Dedupe by normalized arXiv id without version suffix.
- Filter obvious noise such as chemical/biological/contrast agents.
- 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
- 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/
