Capturing Ideas Fast
Quickly capture task ideas without breaking your flow
This section describes common usage patterns that combine the CLI tools and code agent skills into end-to-end development workflows.
The full task lifecycle — capturing ideas quickly, wrapping ad-hoc work into tracked tasks, decomposing large items into children, and consolidating overlap.
Running multiple tasks side by side, front-loading planning work, and farming out execution to remote web sandboxes.
Keeping the codebase correct and understandable — structured code review, test coverage analysis, and tracing why existing code exists.
Round-tripping with issue trackers, pull requests, upstream contributions, releases, and reverts — the flows that cross aitasks’ boundary with the wider git ecosystem.
Next: Code Agent Skills
Quickly capture task ideas without breaking your flow
Wrap ad-hoc changes into the aitasks framework after the fact
Breaking complex tasks into manageable child subtasks
Merging overlapping or duplicate tasks into a single actionable task
Round-trip workflow between issue trackers (GitHub, GitLab, Bitbucket) and aitasks
End-to-end guide for creating aitasks from pull requests
End-to-end guide for sharing changes and managing incoming contributions with aitasks
Working on multiple tasks simultaneously with concurrency safety
Front-load complex task design work while other implementations run in parallel
Running tasks on Claude Code Web with sandboxed branch access
Creating follow-up tasks, querying existing tasks, and updating them with new findings — all during implementation
Browse source files, select a line range, and spawn a task pre-seeded with a file reference — with optional auto-merge of overlapping pending tasks.
Systematic code review using review guides, separate from implementation
Start with codebase exploration, create tasks from findings
Systematic test coverage analysis and follow-up task creation
Human-checked verification items (TUI flows, live agent launches, artifact inspection) as first-class gated tasks
Automated changelog generation and release pipeline from task data
Use code evolution history to rebuild understanding of why code exists
Reverting features or changes that are no longer needed