context-management

Name: context-management
Rating: 5 (4 reviews)
Author: VersoXBT

Strategies for managing AI agent context windows including optimization, summarization, retrieval-augmented generation, progressive disclosure, and pruning. Use when the user is hitting context limits, building long-running agents, implementing RAG, optimizing token usage, or designing systems that need to manage large amounts of information within limited context windows.

4stars

Updated last month

View on GitHub ↗License: MIT

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Context Management

Strategies for optimizing AI agent context windows. Covers summarization, RAG, progressive disclosure, pruning, and token budgeting for long-running agents.

When to Use

User is hitting context window limits in agent workflows
User is building long-running agents that accumulate context
User needs retrieval-augmented generation (RAG) patterns
User wants to optimize token usage and reduce costs
User is designing memory systems for agents

Core Patterns

S

[Description truncada. Veja o README completo no GitHub.]

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