OthmanAdi/planning-with-files
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60+ agents.
What it solves
AI coding agents often suffer from "volatile memory," where their task plans and progress are lost when the context window is reset (e.g., via /clear), during compaction, or after a crash. This leads to goal drift, repeated mistakes, and the need for the user to manually restate goals.
How it works
Instead of keeping a to-do list in the volatile context window, this project implements a "filesystem as memory" approach. It maintains three persistent Markdown files on disk:
task_plan.md: Tracks phases, checkboxes, and the current resume point.findings.md: Stores research notes and decisions.progress.md: Logs session activity and test results.
Lifecycle hooks (such as UserPromptSubmit or SessionStart) automatically re-inject the relevant plan context from these files back into the agent's window at the start of each turn, ensuring the plan survives context loss and remains in the model's attention window.
Who it’s for
Developers using AI coding agents (such as Claude Code, Cursor, GitHub Copilot, or Hermes Agent) for long-running, complex tasks that require persistence across sessions or context resets.
Highlights
- Persistence: Plans survive
/clearcommands, crashes, and context compaction. - Agent Agnostic: Compatible with 60+ agents via the Agent Skills standard and native plugins for several major tools.
- Goal Stability: Prevents goal drift by re-injecting the plan head every turn.
- Integrity Checks: Uses SHA-256 attestation to detect if the plan has been silently tampered with.
- Completion Gating: Can prevent an agent from declaring a task "done" until all phases in the disk-based plan are marked complete.
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