Agented

This skill addresses the lack of reliable history and concurrency control when AI coding agents edit files. In real-world development, when an AI needs to modify the same file across multiple steps, standard editors cannot track each version of the change, easily leading to conflicts or lost work. Agented employs a stateful design, versioned undo trees, and concurrency validation, enabling AI to safely perform multi-step edits. Even if a file is modified by another agent, changes are detected promptly, allowing for retries.

Usage is straightforward: simply install the ae command in your terminal and open a file with ae open <path> to begin editing. You can then use natural language instructions to perform operations like read, replace, insert, and write. All modifications are automatically versioned, supporting undo, branching, and jumping. Each read returns a state_token; when writing, using --expect ensures the file hasn't been modified by another agent. If a conflict occurs, new content and a new token are automatically returned, eliminating the need for manual "read-then-write" cycles.

It is particularly well-suited for AI agent scenarios requiring long-term, multi-step editing of code or documents, especially for teams or individuals needing safe concurrent editing and historical change tracking. For example, when AI automatically fixes code defects in CI/CD pipelines or iteratively implements suggestions after code review, Agented ensures every step is documented and prevents data loss due to conflicts.

It is recommended to use this tool uniformly when AI agents edit files, particularly in multi-agent collaboration or scenarios requiring frequent retries. Note that it primarily handles plain text files and does not support binary files (e.g., images, compiled artifacts). Additionally, files must be registered via ae open before first use; subsequent Read and Edit operations will then synchronize with the editor state. Otherwise, concurrency warnings may occur.