What You’ll Learn
- Understanding context windows and their limits
- Selecting files strategically for optimal context
- Recognizing and responding to context overload
- When to reset context for better performance
Understanding Context Windows
Verdent’s context window size depends on the model being used. Extended context (1M) is handled automatically when needed. Available Models:| Provider | Model | Context |
|---|---|---|
| Anthropic | claude-opus-4.5 | 200K |
| Anthropic | claude-sonnet-4.5 | 200K |
| Anthropic | claude-haiku-4.5 | 200K |
| gemini-3-pro-preview | 1M | |
| gemini-3-flash-preview | 1M | |
| OpenAI | gpt-5 | 272K |
| OpenAI | gpt-5-codex (Beta) | 272K |
| Zhipu AI | GLM 4.7 | 200K |
| Moonshot | kimi-k2-turbo | 262K |
- All messages in conversation
- File contents loaded into context
- Tool outputs and responses
- System prompts and instructions
Viewing Context Usage
Monitor your current context window usage through the Context Remaining indicator in the middle panel. This shows how much context space remains for the current conversation. Context Commands:| Command | Description |
|---|---|
/compact | Compress conversation history to free up context space |
/clear | Clear conversation and start fresh |
Strategic File Selection
Be strategic about file selection to optimize context usage.- @-Mentions
- Best Practices
Use @-mentions for explicit file inclusion:Verdent auto-loads related files, but @-mentions ensure precise control. Only include files directly relevant to the current task.
Recognizing Context Overload
- Response Quality
- Speed Issues
- Behavioral Changes
Signs:
- Less accurate or incomplete responses
- Missing important details from earlier in conversation
- Confused about recent changes or context
When to Reset Context
- Performance Issues
- Task Transitions
- After Commits
- Noticeably slower response times
- Less accurate or inconsistent responses
- Verdent forgetting earlier context