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,...

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Summary Information

Updated 7 minutes ago
Added to GitGenius on September 1st, 2026
Created on January 3rd, 2026
Open Issues & Pull Requests: 8 (+0)
GitHub issues: Enabled
Number of forks: 2,225
Total Stargazers: 26,701 (+0)
Total Subscribers: 118 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 7.0 hours
Mean response time: 37.6 hours
90th percentile: 4.4 days
Tracked items: 128

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 9% of issues opened in the past year have been closed. Three people close 92% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 8
New in 7 days: 5
Closed in 7 days: 5
Avg open age: 85 days
Stale 30+ days: 4
Stale 90+ days: 0

Recent activity

Opened in 7 days: 5
Closed in 7 days: 5
Comments in 7 days: 2
Events in 7 days: 10

Top labels

  • good first issue (8)
  • documentation (4)
  • enhancement (4)
  • bug (2)
  • help wanted (1)

Detailed Description

Planning with Files is an agent skill that provides persistent file-based planning for AI coding agents and long-running tasks.

The tool solves the problem of context loss in AI agents by maintaining three markdown files on disk—task_plan.md, findings.md, and progress.md—that survive context window resets, /clear commands, crashes, and compaction. Rather than relying on prompts the agent might follow, it uses lifecycle hooks that fire every turn to inject planning context back into the agent's working memory. This approach keeps the plan persistent while the agent's context window dies, allowing recovery to read only project files without requiring replay of session records unless explicitly requested through a catchup mode.

The tool suits developers working with long-running autonomous agents across multiple coding platforms. It installs as an agent skill compatible with over 60 agents including Claude, Cursor, Codex, and GitHub Copilot, available through npm, the Claude Code plugin marketplace, or npx. The three-file pattern separates task planning, findings, and progress tracking, creating a deterministic completion gate that prevents context rot from derailing multi-turn agent work.

The project shows active maintenance with blind A/B testing demonstrating measurable improvements in agent task completion. Development includes comprehensive evaluation documentation and a full installation guide, indicating sustained attention to both functionality and user onboarding.