What does gengscan do?
AI-assisted screening for data-integrity fingerprints in scientific papers
- Source: https://github.com/xntj-ai/gengscan
- GitHub stars: 1
- Last pushed: 2026-06-16T10:15:31Z
- Added by Awesome Skills daily skill hunter on 2026-06-16.
AI-assisted screening for data-integrity fingerprints in scientific papers
This skill provides an AI-driven pipeline for screening data-integrity fingerprints in scientific papers. It helps researchers, reviewers, and publishers detect potential fabrications such as image duplications, textual inconsistencies, and statistical anomalies. The skill is sourced from the open-source repository xntj-ai/gengscan on GitHub and can be integrated into AI agent workflows (e.g., Claude Code, Cursor, Codex) as a custom tool. It automates the tedious process of manual integrity checks, improving the efficiency and reliability of scientific peer review.
npx skills add xntj-ai/gengscanInstalled? Explore more Research & Data Analysis skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
AI-assisted screening for data-integrity fingerprints in scientific papers
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.