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Measures cognitive load from task descriptions using transformer-based NLP classification, then visualizes your mental capacity across four zones (Clear, Caution, Warning, Overload) with real-time gauges and AI-powered suggestions. Built with React, TypeScript, and Xenova Transformers for client-side ML inference, it tracks daily patterns, defers overwhelming tasks, and provides actionable insights without server dependencies. Perfect for developers, knowledge workers, and anyone managing complex workloads who want data-driven task prioritization. Licensed under Tetrees License.
CogniLoad is an AI-powered cognitive load estimator that helps developers and knowledge workers track, manage, and optimize their mental workload. The application uses machine learning to classify tasks by cognitive complexity, visualize load distribution across different zones, and provide intelligent suggestions for workload management.
Built with React, TypeScript, and Tailwind CSS, it features a modern dashboard interface with real-time load tracking, task management, historical analytics, and AI-driven insights.
npm install
격리된 샌드박스를 띄워 서버에서 바로 실행하세요 — 로컬 설정 불필요.
이 제품을 AI IDE, 웹 빌더 또는 클라우드 IDE로 바로 가져오세요.
Download your licensed source snapshot from the library, then follow the setup guide in your workspace.
아직 리뷰가 없습니다.
토론을 불러오는 중…
npm run dev
Starts the Vite development server at http://localhost:5173
npm run build
Generates optimized production build in the dist/ directory
npm run typecheck
Validates TypeScript without emitting files
npm run lint # Check for issues
npm run lint:fix # Auto-fix issues
The application uses a dark theme with:
Built-in error boundary with:
Tetrees License
샌드박스 검증이 완료되었으며 감지된 실행 경로가 통과했습니다.
This React web app completed archive review with strong static results. Structure, dependency manifests, documentation, functional source, and common risk patterns were checked by the Tetrees verification pipeline; runtime phases are stated separately. Final verified scores after isolated runtime evidence: overall 8.5 and security 9. Final verified scores after isolated runtime evidence: overall 8.5 and security 9. Final verified scores after isolated runtime evidence: overall 8.5 and security 9. Final verified scores after isolated runtime evidence: overall 8.5 and security 9. Final verified scores after isolated runtime evidence: overall 8.5 and security 9. Final verified scores after isolated runtime evidence: overall 8.8 and security 9.
Deterministic AVCP artifact review
파이프라인 avcp-2026-08-04.1 · SHA-256 471b3f14e4ab2570…
This version-scoped review deterministically inspects the submitted archive for structure, dependencies, documentation, functional source, and common malicious or high-risk signals. Build and test phases are reported as passed only after an isolated sandbox audition. It is not a guarantee of perfect security.
검토일 2026년 8월 7일
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