Claude Scholar is a semi-automated research assistant for academic research and software development, supporting literature review, coding, experiments, reporting, writing, and project knowledge management. Computer science and AI researchers use it across the research workflow with several coding-agent platforms; the catalogue contains its skills, commands, agents, hooks, plugin, and instruction.
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.
npx skills add Galaxy-Dawn/claude-scholar --skill daily-paper-generatorgit clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholarWrote 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.
[](https://agentmods.dev/skills/galaxy-dawn/claude-scholar/daily-paper-generator)<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/daily-paper-generator"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/daily-paper-generator/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.
<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/daily-paper-generator"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/daily-paper-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.01037 |
| Opus 5.5 | $0.00019 | $0.00415 |
| Sonnet 5.5 | $0.00009 | $0.00207 |
| Haiku 4.5 | $0.00005 | $0.00104 |
Grade A, and why
daily-paper-generator 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 1mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Paper Generator
Overview
Discover, screen, and summarize recent papers for any research topic.
Supported sources:
- arXiv
- bioRxiv
- both (
--source both)
Core workflow:
- Define topic query and time window
- Search papers from arXiv / bioRxiv
- Select Top 10 candidates per field
- Score and narrow to Top 3 per field
- Choose Top 1 per field
- Generate bilingual summaries
- Save outputs to
daily paper/
When to Use
Use this skill when:
- The user asks for a daily/weekly paper digest on any topic
- The user wants recent papers from arXiv and/or bioRxiv
- The user needs structured bilingual notes for reading and tracking
Output Format
Each summary should contain:
- Paper title
- Authors and venue/source
- Link(s) and date
- Chinese review (~300 words)
- English review (concise academic prose)
- Metadata table
- Appendix (optional resources)
Quick Reference
| Task | Method |
|---|---|
| Search papers | Use scripts/arxiv_search.py with `--source arxiv |
| Topic selection | Use general-topic queries from references/keywords.md |
| Evaluate quality | Use references/quality-criteria.md |
| Write Chinese review | Use references/writing-style.md |
| Write English review | Follow scientific writing best practices |
Workflow
Step 1: Define query
Choose a concrete topic query. Examples:
test-time adaptation for medical imagingmultimodal foundation model for healthcareprotein language model interpretability
Step 2: Search arXiv and/or bioRxiv
Use helper script:
python skills/daily-paper-generator/scripts/arxiv_search.py \
--query "test-time adaptation for medical imaging" \
--source both \
--months 1 \
--max-results 80 \
--output /tmp/papers.json
Notes:
--source arxiv: arXiv only--source biorxiv: bioRxiv only--source both: merge both sources and sort by date
Step 3: Top 10 candidate selection (per field)
For each candidate paper:
- Check topic relevance from title + abstract
- Remove obviously off-topic papers
- Keep Top 10 candidates for this field
What ships with it
5 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.
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.
- 1mo ago First seen · 145 lines · 47 tokens per session scan A 5a3bd2fbebd2
daily-paper-generator is a skill published in the GitHub repository Galaxy-Dawn/claude-scholar (5,917 stars, last pushed 8d ago), licensed MIT. It adds 47 tokens to every session and 1,037 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 2026-08-30.
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