Backlog.md

Backlog.md is an innovative automation tool designed to enhance project collaboration in a Git ecosystem by bridging the gap between human teams and AI agents. This Claude Code skill allows users to manage tasks and documentation effectively using Markdown files, facilitating seamless collaboration. By integrating AI agents, teams can automatically generate tasks for new features based on AI insights, ensuring that no critical steps are overlooked during the development process. One of the key benefits of Backlog.md is its ability to visualize project progress through a terminal Kanban board, providing quick status updates that keep all team members informed. While specific time savings are not quantified, the skill is designed to streamline workflows, potentially reducing the time spent on task management and documentation. The integration with AI agents allows for real-time task assignment and tracking, ensuring that projects stay on track and that team members are aligned with their responsibilities. This skill is particularly beneficial for developers, product managers, and AI practitioners who are looking to optimize their workflow automation. It is suitable for teams that operate within a Git environment and require a structured approach to manage tasks and documentation. With a medium GTM relevance, Backlog.md is an excellent addition for organizations aiming to adopt AI-first workflows and leverage automation to enhance productivity. Implementing Backlog.md is straightforward, with an estimated setup time of just 30 minutes. While the skill is classified as intermediate in difficulty, it requires no extensive prior knowledge of AI or automation tools. The practical use cases include exporting project boards as Markdown reports for stakeholder sharing and visualizing progress, which can significantly improve communication and transparency in project management. By incorporating Backlog.md into your workflow, you can harness the power of AI to enhance collaboration and drive project success.

[{"step":"Install Backlog.md in your repository by running `npm install -g backlog-md` or using the VS Code extension. Ensure you have a `.backlog.md` file in your project root.","tip":"Run `backlog-md init` to generate a starter template with common sections."},{"step":"Populate the Backlog.md file with epics, user stories, and tasks using the provided structure. Use GitHub issue links to connect tasks to actual issues.","tip":"Use markdown checkboxes ([ ]) to track progress directly in the file. Link to related PRs with `[PR #123](link)`."},{"step":"Sync your Backlog.md with GitHub/GitLab by running `backlog-md sync` or using the CI/CD integration. This will update issue statuses based on task completion.","tip":"Configure the sync to run on `git push` for real-time updates. Use `backlog-md status` to visualize your Kanban board in the terminal."},{"step":"Collaborate with your team by assigning tasks directly in Backlog.md or via GitHub issues. Use the markdown format to keep discussions and updates in one place.","tip":"Add labels like `(Priority: HIGH)` or `(Estimate: 5 points)` to tasks for better prioritization. Use emojis (🚀, 🔥) for quick visual cues."},{"step":"Use AI agents to automate task creation or updates. For example, run `backlog-md ai \"Generate tasks for implementing OAuth2\"` to get AI-suggested tasks based on your project context.","tip":"Train the AI on your project's codebase by providing context like `backlog-md ai \"Add tasks for refactoring the payment service\" --context ./src/payment-service`."}]