What kind of data does it preserve during compaction?

It prioritizes critical state, completed features, key architectural decisions, and the current task list while compressing more verbose or repetitive information.

When does the skill trigger a summary?

The skill monitors context usage and typically creates a compact summary at 85% capacity, forcing a full session handoff if usage exceeds 90%.

How do I implement it in my project?

You can integrate it by importing the ContextCompactor from the scripts directory and calling the 'should_compact' and 'create_compact_summary' methods in your workflow.

Does this skill work with other Claude Code tools?

Yes, it is designed to integrate seamlessly with session managers and handoff creators to provide a continuous, automated workflow for long-running tasks.

What is the primary goal of the AC Context Compactor?

The primary goal is to prevent Claude from losing critical project information by monitoring context usage and creating compact, structured summaries before the limit is reached.

AC Context Compactor

Name: AC Context Compactor
Author: adaptationio

byadaptationio

Productivity & Workflow

Optimizes Claude's context window by summarizing session history and preserving critical state for long-running tasks.

About

AC Context Compactor is a specialized utility designed to manage the context limits of Claude Code during intensive, multi-session development projects. By proactively monitoring token usage, the skill automatically generates structured summaries when context reaches 85%, ensuring that critical architectural decisions, progress metrics, and pending actions are preserved. It streamlines the transition between sessions by compressing verbose logs into actionable JSON metadata, preventing the model from losing focus or performance as the conversation grows.

Key Features

Automated context monitoring with 85% and 90% threshold triggers
Intelligent extraction of key technical decisions and completed features
Seamless integration with session management and handoff workflows
Selective compression of verbose information to maximize token efficiency
Structured JSON summary generation for state persistence
0 GitHub stars

Use Cases

Preparing structured handoff summaries for different AI agents or human collaborators.
Maintaining continuity during large-scale application refactors that span multiple days.
Optimizing token usage in complex debugging sessions to keep critical code context relevant.

About

Key Features

Automated context monitoring with 85% and 90% threshold triggers
Intelligent extraction of key technical decisions and completed features
Seamless integration with session management and handoff workflows
Selective compression of verbose information to maximize token efficiency
Structured JSON summary generation for state persistence
0 GitHub stars

Use Cases

Preparing structured handoff summaries for different AI agents or human collaborators.
Maintaining continuity during large-scale application refactors that span multiple days.
Optimizing token usage in complex debugging sessions to keep critical code context relevant.