dex enables AI agents to track and manage complex, multi-session tasks with persistent memory. Operations teams benefit from structured task management, capturing full context including descriptions, background, requirements, and approach. It integrates with Claude agents to streamline workflows and improve task completion rates.
git clone https://github.com/dcramer/dex.gitThe dex skill is an innovative automation tool designed specifically for task tracking within AI agents. By integrating dex into your workflow, you can streamline the management of tasks, ensuring that your AI agents operate more efficiently and effectively. This skill allows users to monitor and track the progress of various tasks assigned to AI agents, making it easier to manage workloads and enhance productivity. One of the key benefits of using dex is its ability to save time by automating the tracking process. While the exact time savings are currently unknown, the reduction in manual oversight and the ability to quickly assess task statuses can significantly enhance operational efficiency. Developers, product managers, and AI practitioners will find dex particularly useful, as it provides a structured approach to managing tasks within AI-driven workflows, ultimately leading to better project outcomes. Practical use cases for dex include managing software development tasks, tracking progress on AI model training, or overseeing multiple AI agents working on different projects. For instance, a product manager could utilize dex to monitor the status of feature development across various AI agents, ensuring that deadlines are met and resources are allocated effectively. The intermediate implementation difficulty means that users should have some familiarity with automation tools and AI workflows, but the skill can be set up in approximately 30 minutes, making it accessible for teams looking to enhance their operational capabilities. Incorporating dex into your AI-first workflow not only improves task management but also aligns with the growing trend of AI automation in various industries. As organizations increasingly rely on AI agents to handle complex tasks, having a robust tracking system like dex will be essential for maximizing the potential of these technologies. By utilizing this skill, teams can ensure that their AI agents are not only effective but also aligned with overall business objectives.
[{"step":"Initialize a new task in dex by providing a clear description, background, requirements, and approach. Use the prompt template to structure your input.","tip":"Be specific with requirements and constraints. Include any known dependencies or prerequisites that might affect the task."},{"step":"Break the task into logical steps that can be completed sequentially. Assign each step a clear description and expected output.","tip":"Use the 80/20 rule: focus on the 20% of steps that will deliver 80% of the value. Avoid over-engineering the step breakdown."},{"step":"Execute the first step and update dex with the output, status, and any notes. Use the task ID to maintain continuity across sessions.","tip":"Include specific metrics or data points in the output (e.g., 'Processed 5,000 records with 99% success rate'). This makes progress easier to track."},{"step":"When resuming the task in a new session, query dex using the task ID to retrieve the full context and current status. Pick up where you left off.","tip":"Use dex's query capabilities to filter tasks by status (e.g., 'in_progress' or 'pending') to quickly find what needs attention."},{"step":"After completing the task, generate a summary report in dex with final outputs, lessons learned, and any recommendations for future similar tasks.","tip":"Include metrics like time spent, success rate, and any issues encountered. This builds institutional knowledge for your team."}]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/dcramer/dexCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use dex to track and manage the multi-step task: '[TASK_DESCRIPTION]'. Include the following details: background context '[BACKGROUND]', specific requirements '[REQUIREMENTS]', and preferred approach '[APPROACH]'. Ensure the task is broken into actionable steps with persistent memory across sessions. Update progress in dex after each step is completed.
```json
{
"task_id": "dex-2024-0872",
"title": "Migrate legacy CRM data to new platform",
"status": "in_progress",
"steps": [
{
"step_id": "1",
"description": "Extract data from legacy CRM (Salesforce) using DataLoader API",
"status": "completed",
"output": "Extracted 12,487 contact records and 8,231 opportunity records. Validated 98% data integrity.",
"timestamp": "2024-05-15T14:30:00Z",
"notes": "Used Salesforce DataLoader with custom field mapping. No errors reported."
},
{
"step_id": "2",
"description": "Transform data to match new CRM schema (HubSpot) using Python scripts",
"status": "in_progress",
"output": "Script running. 6,245/12,487 records transformed (50% complete).",
"timestamp": "2024-05-15T15:45:00Z",
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