Paper Pick

${var} — Research topic to search for (e.g. "transformer architectures", "memory consolidation", "RL agents"). If empty, browses today's trending papers.

Read memory/MEMORY.md for context.
Read the last 7 days of memory/logs/ to avoid recommending papers already covered.

Steps

1. Search for recent papers using Hugging Face Papers API (free, no key needed, no rate limits):

   If ${var} is set — search for that topic:

   curl -s "https://huggingface.co/api/papers/search?q=${var}&limit=15"

   If ${var} is empty — browse today's trending papers:

   curl -s "https://huggingface.co/api/daily_papers?limit=15"

   Response is a JSON array. Each entry has:

   • paper.id — arXiv ID (use for links: https://arxiv.org/abs/{id}, PDF: https://arxiv.org/pdf/{id})
   • paper.title, paper.summary (abstract), paper.authors[].name
   • paper.publishedAt — publication date
   • paper.upvotes — community upvotes (higher = more notable)
   • paper.ai_summary — AI-generated summary (on daily papers)

2. If the search returned thin results or ${var} is a niche topic, also try WebSearch for "[topic] paper $(date +%Y) site:arxiv.org" to catch papers the API missed.

3. From all results, pick the single best paper — the one most worth reading today. Criteria: novelty, relevance, practical implications, community signal (upvotes). Skip anything already mentioned in recent logs.

4. Send via ./notify:

   *Paper Pick — ${today}*
   
   "Paper Title" — Authors · ↑upvotes
   One sentence: why this paper is worth your time.
   [Read](https://arxiv.org/abs/ID) | [PDF](https://arxiv.org/pdf/ID)

5. Log to memory/logs/${today}.md.

If nothing interesting found, log "PAPER_PICK_OK" and end.

Sandbox note

The sandbox may block outbound curl. Use WebFetch as a fallback for any URL fetch. For auth-required APIs, use the pre-fetch/post-process pattern (see CLAUDE.md).