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Manage collaborative AI agent tasks with lightweight tracking, queues, subtasks, and comments.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "tinytask" yet — see the docs or source repo.
Use tinytask to create a development task queue for 'Build user login feature'. Split it into three subtasks: API development, frontend page, and unit testing. Make unit testing depend on the first two tasks, and add owner notes for each task.
A task structure with parent task, subtasks, dependencies, and notes for coordinated multi-agent execution.
Use tinytask to set up a research task list with 'Collect papers', 'Organize datasets', and 'Write conclusions'. Mark 'Write conclusions' as blocked by the first two tasks, and record current progress and next steps in comments.
A trackable research task list with clear blocking relationships and progress comments for collaboration.
Use tinytask to create a product request queue with 'Organize user feedback', 'Define requirement priorities', and 'Draft PRD'. Put them into a sequential queue and add comments describing the expected output for each.
A sequential product task queue with output notes, making ongoing collaboration with AI assistants easier.
Manage tasks through an AI agent and delegate work by email.
Add an agent-native context layer to your task app for better memory.
Track, update, and manage shared tasks through a simple TASKS.md file.
Manage tasks in a terminal Kanban board for humans and AI agents.
Provide token-light local memory and SQLite hybrid retrieval for MCP agents.
Manage tasks and projects with prioritization, estimation, and agile progress tracking.