A task-aware context compression system for AI assistants that efficiently reduces token usage in long conversations while preserving essential information through a multi-level compression pipeline.

With the widespread adoption of AI programming assistants (such as Cursor and Claude Code), developers are enjoying unprecedented improvements in productivity. However, have you encountered this common challenge: after multiple rounds of conversation, the context becomes excessively long, token usage skyrockets, responses slow down, and costs surge dramatically?

Today, I am pleased to introduce a solution built on the Skills Framework — Task-Aware Compression Skill (task-aware-compression).

Skills is a powerful extension framework for AI assistants that enables developers to add specialized capabilities through declarative configuration. Each Skill is an independent functional module that can be invoked on-demand during conversations, making AI assistants more intelligent and efficient.

Simply put, it is an intelligent context compression system that maximizes context token reduction without compromising task completion quality.

Core Principles: Task-First, Structure-First, Deferred Compression.

The system provides three compression modes designed for different scenarios:

Unlike crude truncation approaches, task-aware compression:

• Protects Recent Window: Preserves the most recent 3-5 conversation turns verbatim to prevent loss of immediate context
• Task-Aware Extraction: Retains only information directly relevant to current objectives
• Structured Storage: Converts natural language into compact JSON/YAML formats

Original Context
  ↓
[0] Preserve Recent Window
  ↓
[1] Noise Filtering (remove redundancy)
  ↓
[2] Importance Scoring (task relevance)
  ↓
[3] Task-Aware Summarization
  ↓
[4] Structured Compression
  ↓
[5] Self-Validation (prevent over-compression)

Consider a 20-turn conversation about "implementing user authentication":

Original Context: ~800 tokens

After Light Mode: ~480 tokens (retaining key conversations)

After Medium Mode: ~120 tokens (compressed to structured configuration)

{
  "auth": {
    "method": "JWT",
    "remember_me": true,
    "token_expiry": "24h"
  },
  "ui": {
    "style": "minimal"
  },
  "features": {
    "captcha": false,
    "error_messages": true
  }
}

Achieving 85% compression ratio while preserving all critical requirements intact.

• Heavy AI Programming Assistant Users: Dozens of daily conversation turns with AI
• Cost-Conscious Users: Seeking to reduce API calling costs
• Performance Optimizers: Requiring faster AI response speeds
• Agent Developers: Building AI Agents that require long-term memory

As a Skill within the Skills Framework, you can easily integrate it into your environment:

1. Add Skill to Your Skills Directory

   cp -r task-aware-compression ~/.cursor/skills/

2. Invoke During Conversation When conversation context becomes too long, simply type:

   /task-aware-compression
   

3. Specify Compression Level

   Compress current conversation context using medium mode, with the objective "implementing user authentication"
   

• Comprehensive Design Documentation (plan.md)
• Ready-to-Use Prompt Templates (references/)
• Real-World Test Cases (examples/)
• Python Validation Scripts (examples/verify_compression.py)
• Skill Configuration File (SKILL.md)

Visit the project repository to explore this skill that makes AI conversations more efficient!

The Skills Framework provides unique advantages for AI assistant extensions:

• Modular Design: Each Skill is an independent functional unit, easy to develop and maintain
• Plug-and-Play: Simple directory structure, copy-to-use, no complex configuration required
• Task-Oriented: Skills focus on solving specific problems, such as context compression in this project
• Composable: Multiple Skills can work collaboratively to build powerful AI workflows
• Community-Driven: Open ecosystem encouraging developers to contribute their own Skills

This project embodies the Skills Framework philosophy perfectly: addressing real-world AI assistant pain points through a carefully designed Skill.

Make Every Conversation Count.

Project: task-aware-compression