Handover

For long tasks, handover lets you reset context without losing track of progress.

Manual handover

Use /handover to trigger a handover. The model summarizes what it's done, the conversation is cleared, and a fresh context starts with the summary, a current file tree, and any instructions you provide:

> /handover now write tests for the auth module

This is useful when context is getting long and you want to refocus the model on the next phase of work.

Auto-handover

nav can automatically trigger a handover when the conversation approaches the model's context window limit. This prevents context overflow errors and keeps the model working effectively.

How it works

1. nav tracks token usage after each response
2. When usage crosses the threshold (default: 80% of the context window), a handover is triggered
3. The agent completes its current step, generates a summary, and continues in a fresh context
4. If the threshold is reached after the model finishes responding, the auto-handover triggers on the next user message

Configuration

# Override context window (e.g. for LM Studio or custom endpoints)
export NAV_CONTEXT_WINDOW=32768

# Trigger auto-handover at 90% instead of the default 80%
export NAV_HANDOVER_THRESHOLD=0.9

Context window detection

Context window sizes are auto-detected per provider:

Provider	Detection method
OpenAI / Anthropic / Gemini	Built-in table of known models
Ollama	Queried from the Ollama API at startup
LM Studio / custom	Set manually via NAV_CONTEXT_WINDOW

Verbose mode

In verbose mode (-v), each response shows context utilization:

tokens: 45.2k in / 1.2k out (3.1s) (35% of 128k ctx)