xianshang33/llm-paper-daily/paper-daily

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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.

Install

npx vskill@latest install xianshang33/llm-paper-daily/paper-daily

SKILL.md

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
  1. 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:

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

Write JSON output:

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

For local testing with fewer requests:

bash
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:

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

Manually publish specific arXiv IDs with an explicit display date:

bash
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:

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

Generate only the canonical/feed outputs:

bash
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/

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
1,330
Repository forks
60
7-day trend score
36

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