How does AC Context Optimizer save tokens?

It identifies and removes low-priority information from the context window, ensuring only essential data is sent to the model, which reduces overhead and costs.

Does this require manual configuration?

While it provides an API for specific needs, it can autonomously analyze and prioritize context based on your project directory structure.

Can I use this with large repositories?

Yes, it is specifically designed to handle large codebases by prioritizing files and snippets most relevant to the current task while staying within limits.

What is the benefit for autonomous agents?

It prevents 'context drift' and ensures the agent doesn't lose focus on its primary objective due to information overload from irrelevant files.

Autonomous Context Optimizer

Name: Autonomous Context Optimizer
Author: adaptationio

byadaptationio

Productivity & Workflow

Streamlines token usage and prioritizes critical information to maximize the efficiency of autonomous coding agents within context window limits.

About

The AC Context Optimizer is designed to solve the challenges of context window management in autonomous coding environments. By intelligently prioritizing relevant data and pruning unnecessary information, this skill ensures that Claude stays focused on high-priority tasks while reducing token consumption. It is particularly useful for large-scale codebases where full context inclusion is impossible, allowing the agent to maintain peak performance and reasoning accuracy without hitting architectural constraints.

Key Features

Project-wide context optimization
Token usage reduction
0 GitHub stars
Automated pruning of irrelevant data
Information prioritization logic
Intelligent context window management

Use Cases

Reducing API costs by minimizing unnecessary token transmission
Managing large-scale refactors where the codebase exceeds context limits
Improving model reasoning by focusing on high-priority code segments

About

Key Features

Project-wide context optimization
Token usage reduction
0 GitHub stars
Automated pruning of irrelevant data
Information prioritization logic
Intelligent context window management

Use Cases

Reducing API costs by minimizing unnecessary token transmission
Managing large-scale refactors where the codebase exceeds context limits
Improving model reasoning by focusing on high-priority code segments