Automation

Keeps task_plan.md, findings.md and progress.md on disk so an agent's multi-step work survives /clear, compaction and context loss.

Turns complex work into three persistent markdown files — task_plan.md, findings.md, progress.md — so the agent plans, logs, and recovers context reliably.

Gives AI agents persistent on-disk working memory through task_plan.md, findings.md and progress.md so multi-step work survives context loss.

Keeps task_plan.md, findings.md and progress.md on disk as the agent's persistent working memory for multi-step work.

Keeps task_plan.md, findings.md, and progress.md on disk so multi-step agent work survives context compaction and session breaks.

Persists agent working memory on disk via task_plan.md, findings.md and progress.md so long multi-step tasks survive context compaction and session breaks.

Keeps task_plan.md, findings.md and progress.md on disk so an agent never loses the thread across long, multi-step work.

Keeps task_plan.md, findings.md, and progress.md on disk as the agent's persistent working memory for multi-step work.

Keeps task_plan.md, findings.md and progress.md on disk so multi-step work survives /clear, compaction and context loss.

Turns complex multi-step work into three persistent Markdown files — task_plan.md, findings.md, progress.md — so context survives compaction and /clear.

A Manus-style planning skill that tracks complex work in task_plan.md, findings.md and progress.md, and restores context automatically after a cleared session.

A Manus-style planning skill that breaks complex work into task_plan.md, findings.md, and progress.md, and restores context automatically after /clear.

Manus-style persistent planning that keeps task_plan.md, findings.md, and progress.md on disk so multi-step work survives context loss and /clear.

Keeps task_plan.md, findings.md, and progress.md on disk so multi-step work survives /clear, compaction, and session breaks.

A Manus-style workflow that keeps task_plan.md, findings.md and progress.md on disk as durable working memory for multi-step tasks, with Arabic-language instructions.

Manus-style planning that keeps task_plan.md, findings.md, and progress.md on disk so multi-step work survives /clear and context compaction.

A German-language planning skill that breaks complex work into task_plan.md, findings.md and progress.md, and restores context automatically after a session is cleared.

A meta-skill that logs friction and user corrections during real work and converts them into skill updates or new-skill proposals at a weekly review.

Install, authenticate and operate Gemini Notebook (NotebookLM) end-to-end through the notebooklm-py CLI or its typed async Python API, with ID-pinned, authorization-aware workflows.

Keeps plans, findings, and progress in markdown files so long multi-step tasks survive context loss and session gaps.