How do I handle slow data fetching in a context provider?

You can use the AsyncContextProvider pattern to refresh data asynchronously before running the agent, ensuring the prompt is updated without blocking the main execution loop.

Can I share context between multiple agents?

Yes, a single context provider instance can be registered to multiple agents simultaneously, allowing them to share and act upon synchronized state.

What is an Atomic Agents Context Provider?

It is a specialized class within the Atomic Agents framework that dynamically injects real-time information into an agent's system prompt during execution.

Does this require modifying the agent's base prompt?

No, context providers inject data into the system prompt dynamically at runtime, allowing the base prompt template to remain clean and static.

Atomic Agents Context Providers

Name: Atomic Agents Context Providers
Author: BrainBlend-AI

byBrainBlend-AI

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5,524

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Data Science & ML

Injects dynamic, runtime data into AI agent system prompts to enable context-aware decision making and information sharing.

The Atomic Agents Context Providers skill enables developers to dynamically augment agent system prompts with real-time information such as user metadata, RAG-retrieved documents, or system state. By decoupling dynamic data from static prompt templates, this skill allows for more flexible agent architectures where information can be updated at runtime and shared across multiple agents. It provides a standardized framework for building context-aware AI applications, ensuring that agents always have access to the most current data without requiring manual prompt engineering for every state change.

Key Features

01Standardized BaseDynamicContextProvider for custom data sources

02Support for asynchronous data fetching and context caching

035,524 GitHub stars

04Dynamic system prompt injection at runtime

05Cross-agent context sharing for coordinated multi-agent systems

06Pre-built patterns for RAG, session management, and database schemas

Use Cases

01Sharing global state or system configurations across a team of specialized AI agents

02Integrating dynamic RAG results into LLM workflows for grounded responses

03Injecting real-time user session data and roles into customer support agents

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add brainblend-ai/atomic-agents atomic-context

For use in Claude.ai and ChatGPT

Download Skill