peer-reviewerAI-powered academic paper reviewer. Uses a multi-agent system (Deconstructor, Devil's Advocate, Judge) to analyze papers for logical flaws, contradictions, and empirical validity.
Install via ClawdBot CLI:
clawdbot install sschepis/peer-reviewerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses sensitive credential files or environment variables
process.env.OPENAICalls external URL not in known-safe list
http://export.arxiv.org/api/query?search_query=${query}&start=0&max_results=5`Uses known external API (expected, informational)
api.openai.comAI Analysis
The skill's external API calls (OpenAI, arXiv) are consistent with its stated purpose of academic paper review, and no hidden instructions or credential harvesting beyond documented configuration are evident. The primary risk is the potential exposure of sensitive user-provided text to these third-party services, which is an inherent function of the skill.
Generated Mar 21, 2026
Researchers can use this skill to pre-review their own papers before submission to journals, identifying logical gaps or contradictions that might lead to rejection. It helps ensure arguments are robust and evidence is properly aligned with claims, saving time in the revision process.
Funding agencies or internal review boards can employ the skill to evaluate grant proposals for methodological soundness and novelty. It checks for empirical validity and consistency with existing literature, aiding in objective decision-making for resource allocation.
Instructors can integrate this skill into coursework to teach critical thinking and scientific writing. Students submit drafts to receive automated feedback on logical flaws, helping them improve argumentation skills and learn peer review standards.
Companies in tech or pharmaceutical sectors can use it to analyze internal research reports or white papers for logical consistency and empirical support. It ensures findings are credible before public release or product development decisions.
Think tanks or government agencies can apply the skill to review policy briefs or scientific reports underlying regulations. It identifies contradictions or weak evidence, enhancing the reliability of policy recommendations based on academic research.
Offer the skill as a cloud-based service with tiered pricing for individuals, institutions, and enterprises. Users upload papers via a web interface or API to receive merit reports, with features like batch processing and integration into existing workflows.
Sell perpetual licenses or annual contracts to universities, research labs, and corporations for on-premise deployment. Includes customization, support, and training services to integrate the tool into internal review processes and compliance systems.
Provide a free basic version for individual users with limited reviews per month, and charge for advanced features like detailed analytics, priority processing, or integration with academic databases. This model attracts a broad user base and upsells to power users.
💬 Integration Tip
Ensure the Node.js environment is set up with proper credentials, and consider wrapping the CLI tool in a simple web interface for easier access by non-technical users.
Scored Apr 19, 2026
Audited Apr 17, 2026 · audit v1.0
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