paper-recommend

paper-recommend is a skill for Claude Code from JeanDiable/obsidian-claude. It costs 40 tokens per session (5,327 once invoked), scanned A, original, MIT.

A daily research assistant that finds recent and popular papers on arXiv, a website for sharing research papers, and Semantic Scholar, a research search service. It scores papers by relevance, age, popularity, and quality, then creates a recommendation note.

In plain words
What is it for?
It helps start a research day by reading configured interests, searching relevant fields, ranking papers, and linking recommendations to existing notes.
Why use it?
It reduces the time needed to find useful new papers and avoids recommending papers already recorded in the notes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the obsidian-claude plugin — 19 skills shipped together

Good fit It helps start a research day by reading configured interests, searching relevant fields, ranking papers, and linking recommendations to existing notes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jeandiable/obsidian-claude/paper-recommend
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add JeanDiable/obsidian-claude --skill paper-recommend
Clone the repo
git clone --depth 1 https://github.com/JeanDiable/obsidian-claude

Made for: Claude Code.

Or install obsidian-claude, the plugin that ships this one along with the rest of its 19 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for paper-recommend

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/paper-recommend/github.svg)](https://agentmods.dev/skills/jeandiable/obsidian-claude/paper-recommend)
Your own site
<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/paper-recommend"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/paper-recommend/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for paper-recommend

Your own site · 80×15
<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/paper-recommend"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/paper-recommend.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,327 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.05327
Opus 5.5 $0.00016 $0.02131
Sonnet 5.5 $0.00008 $0.01065
Haiku 4.5 $0.00004 $0.00533

Measured 2mo ago against content hash 3d2fca10a79b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paper-recommend scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/common_words.py, scripts/link_keywords.py, scripts/scan_existing_notes.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/paper-recommend/SKILL.md · 602 lines

How it starts

The opening of the file, as written. The whole thing — 602 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Daily Paper Workflow Starter.

Goal

Help the user start their research day by searching recent and trending papers from the past month and year, generating a recommendation note.

Workflow

Workflow Overview

This skill uses Python scripts to call arXiv API, parse XML results, and filter/score papers based on research interests.

Step 1: Collect Context (Silent)

  1. Get today's date

    • Determine current date (YYYY-MM-DD format)
  2. Read research config

    • Read $OBSIDIAN_VAULT_PATH/90_System/Config/research_interests.yaml (note: filename is interests not interest) to get research domains
    • Extract: keywords, categories, and priorities
  3. Scan existing notes to build index

    • Scan 50_Clippings/Papers/ directory for all .md files
    • Extract note titles (from filename and frontmatter title field)
    • Build keyword-to-note-path mapping for auto-linking
    • Prefer frontmatter title field, then filename

Step 2: Search Papers

2.1 Search Scope

Search all relevant categories for recent papers:

  1. Search scope

    • Use scripts/search_arxiv.py to search arXiv
    • Query: all research-related arXiv categories
    • Sort by submission date
    • Limit results: 200 papers
  2. Filtering strategy

    • Filter papers based on research interests config
    • Calculate comprehensive recommendation score
    • Keep top 10 high-scoring papers

2.2 Execute Search and Filtering

Use scripts/search_arxiv.py to complete search, parsing, and filtering:

# Use Python script to search, parse, and filter arXiv papers
# First cd to skill directory, then run script
cd "$SKILL_DIR"
python scripts/search_arxiv.py \
  --config "$OBSIDIAN_VAULT_PATH/90_System/Config/research_interests.yaml" \
  --output arxiv_filtered.json \
  --max-results 200 \
  --top-n 10 \
  --categories "cs.AI,cs.LG,cs.CL,cs.CV,cs.MM,cs.MA,cs.RO" \
  --prev-recommendations-dir "$OBSIDIAN_VAULT_PATH/50_Clippings/Papers/Daily" \
  --dedup-lookback-days 30

Read the full file on GitHub · 602 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 602 lines · 40 tokens per session scan A 3d2fca10a79b

Subscribe to this mod's changes

paper-recommend is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 8mo ago), licensed MIT. It adds 40 tokens to every session and 5,327 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

paper-recommend compared with skills from other repositories

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