What does history compaction do?

The /compact command helps reduce the size of your session history, which optimizes token usage and prevents the context window from becoming overloaded during long sessions.

How do I save my progress in NanoClaw?

The skill uses persistent markdown-backed sessions, ensuring your interaction history is saved locally and remains compatible with standard markdown readers.

Can I test multiple approaches without losing my work?

Yes, you can use the /branch command to create a checkpoint of your current session, allowing you to explore different paths or high-risk changes safely.

What is NanoClaw REPL?

NanoClaw REPL is a skill for managing and extending the NanoClaw v2 environment, providing a zero-dependency, session-aware interface for Claude.

NanoClaw REPL Manager

Name: NanoClaw REPL Manager
Author: hieuck

byhieuck

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Developer Tools

Manages and extends NanoClaw v2, a zero-dependency, session-aware REPL for persistent and branched AI interactions.

NanoClaw REPL is a specialized skill designed to operate and extend the NanoClaw v2 environment, a lightweight interaction loop built on Claude. It provides advanced session management capabilities, including markdown-backed persistence, history compaction to optimize token usage, and session branching for risk-free experimentation. This skill is ideal for developers who require a local, extensible, and deterministic way to interact with Claude while maintaining full control over their interaction history and model selection.

Key Features

01Multi-format export capabilities for MD, JSON, and TXT

02On-the-fly model switching and dynamic skill loading

03Session branching for non-destructive experimentation

040 GitHub stars

05Persistent markdown-backed session management

06Token-saving history compaction and cross-session search

Use Cases

01Testing experimental code changes using session branching and restoration

02Archiving and exporting structured AI interactions for documentation or sharing

03Managing long-running development sessions with persistent history

Key Features

01Multi-format export capabilities for MD, JSON, and TXT

02On-the-fly model switching and dynamic skill loading

03Session branching for non-destructive experimentation

040 GitHub stars

05Persistent markdown-backed session management

06Token-saving history compaction and cross-session search

Use Cases

01Testing experimental code changes using session branching and restoration

02Archiving and exporting structured AI interactions for documentation or sharing

03Managing long-running development sessions with persistent history