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by tarunkorat
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
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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
The sandbox audition completed and the detected runnable path passed.
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
Pipeline 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.
Reviewed Aug 7, 2026
The full install guide and integration prompts unlock after purchase.
