Escape the friction of traditional GUI-based tools by building a bespoke task management system that runs in your terminal. This workflow uses Claude Code and markdown files to create and manage your to-do list with simple slash commands and natural language.
with Claire Vo
The system's engine is a custom slash command you create in your terminal. This command, /today, triggers a Python script that you write. The script's job is to scan all of your task files (stored as markdown) and generate a new markdown file for the day, which includes tasks due today, overdue items, and in-progress ideas.
/todayStore every task as a separate .md file inside a local Obsidian vault. This ensures your data is portable and easily accessible by the AI. Use YAML front matter at the top of each file to structure metadata like due_date and tags.
---
type: task
due_date: 2024-08-21
tags:
- sales
- course-launch
---
# Update sales page for the new course
- [ ] Draft new copy for the features section
- [ ] Find new testimonials
- [ ] Update pricing tableInteract with your system conversationally within a dedicated Claude Code window. To add a task, simply type a natural language instruction. Claude will parse your request, create a new markdown file with the correct YAML metadata, and add it to your daily to-do list.
new task, send. Thank you to Claire. do today. How I AI was a blast.
Improve your AI's performance by moving from a single, massive context file to a modular library of small, focused markdown files. This system allows the AI to intelligently load only the most relevant information for each task, enabling you to use simple, 'lazy' prompts and get better results.
Build a custom research assistant that automatically finds relevant academic papers and generates high-quality summaries. This system delivers a daily research digest to your to-do list, helping you stay on top of your field with minimal effort.
Leverage OpenAI Codex for high-level software architecture by using the `Plans.md` technique. This workflow guides the AI to generate a comprehensive, multi-step implementation plan for large projects before writing any code.
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