Que fait AI-research-feedback ?
A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.
A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.
AI-research-feedback is a Claude Code agent skill that a collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.
npx skills add claesbackman/AI-research-feedbackInstalled? Explore more Recherche et analyse de données skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
A collection of Claude Code skills for academic research review. These tools were developed by Claes Bäckman.
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.