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context-optimizer

Prune and prioritize DeepSeek context messages using semantic deduplication and relevance scoring.

Updated Jun 15, 2026
Search Tags:#context management#memory management#context optimization#relevance scoring#DeepSeek
One-click install
npx skills add https://github.com/ironkid90/lucky5-v8 --skill context-optimizer-ironkid90
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: context-optimizer
Source: https://github.com/ironkid90/lucky5-v8/tree/main/plugins/skills/context-optimizer
Command: npx skills add https://github.com/ironkid90/lucky5-v8 --skill context-optimizer-ironkid90

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires deepseek, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

DeepSeek users often struggle with managing their 64k context window, leading to information overload and missed data. This Skill addresses this by optimizing the context window's usage.

Core Features & Use Cases

  • Context Pruning: Automatically manages context by merging, summarizing, and extracting messages.
  • Query-aware Relevance: Prioritizes messages based on their relevance to the current query.
  • Hierarchical Memory System: Implements a context archive to preserve important information while optimizing memory usage.
  • Use Case: For a user frequently engaged in complex discussions, this Skill can help maintain a relevant context without overflow.

Quick Start

Use the context-optimizer skill to manage your DeepSeek context, optimizing it for your current query.

Frequently Asked Questions about context-optimizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize DeepSeek's 64k context window during long conversations?▼

Intelligent context pruning and dynamic relevance scoring automatically merge, summarize, and prioritize messages based on your current query to optimize DeepSeek's 64k context window.

What is context pruning and how does it manage memory overload?▼

Context pruning manages memory overload by automatically merging, summarizing, and extracting older messages, preventing information loss and context overflow in complex discussions.

How does query-aware relevance scoring prioritize messages in DeepSeek?▼

Query-aware relevance scoring prioritizes messages by dynamically evaluating and ranking their semantic relevance to the current query, ensuring the most important information remains active.

Can I use a hierarchical memory system for long-term context storage in DeepSeek?▼

Yes, you can implement a hierarchical memory system that acts as a context archive to preserve important information long-term while optimizing active memory usage.

Does semantic deduplication work for managing DeepSeek context overflow?▼

Semantic deduplication works for managing DeepSeek context overflow by identifying and removing redundant messages, freeing up token space within the 64k context window.

Do I need a specific DeepSeek setup to use context optimization features?▼

You need a DeepSeek environment to use these context optimization features, as the Skill specifically targets and manages the DeepSeek 64k context window architecture.

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