paper-finder

name	paper-finder
description	Discover recent arXiv papers matching a research profile and generate Obsidian-compatible Markdown notes. Use this skill when the user wants to find new papers, refresh their literature inbox, or search arXiv based on their interests.

Paper Finder

Use this skill when you want to discover recent arXiv papers for a specific research profile and write the results as Obsidian-compatible Markdown notes.

Run Retrieval

Run the CLI from the repository root:

python skills/paper-finder/find_papers.py \
  --profile path/to/research-interest.json \
  --output path/to/obsidian/inbox

Optional semantic ranking:

python skills/paper-finder/find_papers.py \
  --profile path/to/research-interest.json \
  --output path/to/obsidian/inbox \
  --semantic

Semantic settings are read from stable-jarvis/.env:

• EMBEDDING_BASE_URL
• EMBEDDING_API_KEY
• EMBEDDING_MODEL

You can pass --semantic-config path/to/config.json for advanced overrides.

Build or Refresh a Profile

If the user does not already have a profile JSON, use Zotero MCP read tools to collect evidence first:

1. zotero_list_collections
2. zotero_profile_evidence

Then write a JSON profile matching the same structure used by config/research-interest.example.json:

• profile_id
• profile_name
• zotero_basis
• retrieval_defaults
• interests[]

Prefer short method_keywords and only a small number of query_aliases per interest.

Write it in temp/paper-finder/research-interest.json, if there is no such directory, create it.

Enrich Candidate Notes

After the Python retrieval run finishes, read the generated Obsidian note and use Zotero MCP read tools to gather nearby library evidence. Then update the note's frontmatter and the Why It Matters, Quick Takeaways, and Caveats sections using the prompt in skills/paper-finder/prompts/enrich-candidate.prompt.txt.