No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by O0000-code · Codex Skill · ★ 131
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is paper-search-pro safe to install? View the security audit →
English · 中文 paper-search-pro Academic literature discovery as a Skill. Built natively for Claude Code; runs in Codex and any agent that loads the SKILL.md format. Five sources · four tiers · single-file Shadcn report. → Live demo (opens the actual report in your browser) What it does You ask your agent for papers; this Skill runs a real multi-source literature search across OpenAlex · Semantic Scholar · CrossRef · PubMed · arXiv, classifies relevance via parallel LLM SubAgents, and writes a self-contained HTML report you can open in any browser. No external LLM keys — your agent is the LLM. CJK in the query routes to Chinese UI; otherwise English. Both report flavor
| Stars | 131 |
| Forks | 8 |
| Language | HTML |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 71.8098215721934/100 |
| Last Updated | 2026-07-14 |
| Created | 2026-05-24 |
| Platforms | claude-code, codex |
| Est. Tokens | ~17k |
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paper-search-pro is Academic literature discovery as a Skill — Claude Code · Codex · any agent that loads SKILL.md. Five sources · four tiers · single-file Shadcn report.. It is categorized as a Codex Skill with 131 GitHub stars.
paper-search-pro is primarily written in HTML. It covers topics such as academic-research, agent-skill, arxiv.
You can find installation instructions and usage details in the paper-search-pro GitHub repository at github.com/O0000-code/paper-search-pro. The project has 131 stars and 8 forks, indicating an active community.
paper-search-pro is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to paper-search-pro on Agent Skills Hub include nature-academic-search, paper-fetch, de-anthropocentric-research-engine. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: