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Accelerate Atomic Agents app development through a guided 7-phase workflow: delegate schema design, agent and tool creation, architecture planning, codebase analysis, and code review to specialized AI sub-agents for scalable multi-agent LLM systems.
npx claudepluginhub brainblend-ai/atomic-agents --plugin atomic-agentsQuickly create a new Atomic Agents agent with proper configuration, schemas, and system prompt
Guided workflow for creating well-organized Atomic Agents applications with schema design, agent configuration, tool implementation, and best practices
Quickly create a new Atomic Agents tool with proper input/output schemas and error handling
Designs Atomic Agents application architectures by analyzing requirements, selecting appropriate patterns, and creating comprehensive implementation blueprints. Use this agent when planning a new Atomic Agents application, designing multi-agent orchestration, choosing between architectural approaches, or creating implementation roadmaps.
Deeply analyzes existing Atomic Agents applications by tracing agent configurations, schema definitions, tool implementations, context providers, and orchestration patterns. Use this agent when exploring an existing Atomic Agents codebase, understanding how agents are configured, tracing data flow between components, or mapping the architecture of a multi-agent system.
Reviews Atomic Agents code for bugs, anti-patterns, security issues, and adherence to framework best practices. Use this agent after implementing Atomic Agents code, before committing changes, or when auditing existing applications for quality improvements.
Generates well-structured Pydantic schemas for Atomic Agents applications, including input schemas, output schemas, tool schemas, and complex nested structures. Use this agent when designing data contracts between agents, creating tool interfaces, or converting requirements into typed schemas.
This skill should be used when the user asks to "create an agent", "configure AtomicAgent", "set up agent", "agent configuration", "AgentConfig", "ChatHistory", or needs guidance on agent initialization, model selection, history management, and agent execution patterns for Atomic Agents applications.
This skill should be used when the user asks to "create context provider", "dynamic context", "inject context", "BaseDynamicContextProvider", "share data between agents", or needs guidance on context providers, dynamic prompt injection, and sharing information across agents in Atomic Agents applications.
This skill should be used when the user asks to "write system prompt", "configure SystemPromptGenerator", "prompt engineering", "background steps output_instructions", "improve agent prompt", or needs guidance on structuring system prompts, writing effective instructions, and optimizing agent behavior in Atomic Agents applications.
This skill should be used when the user asks to "create a schema", "define input/output", "add fields", "validate data", "Pydantic schema", "BaseIOSchema", or needs guidance on schema design patterns, field definitions, validators, and type constraints for Atomic Agents applications.
This skill should be used when the user asks to "create project structure", "organize atomic agents project", "pyproject.toml", "project layout", "directory structure", or needs guidance on organizing files, configuring dependencies, and structuring Atomic Agents applications for maintainability.
Uses power tools
Uses Bash, Write, or Edit tools
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Editorial "Agent Architect" bundle for Claude Code from Antigravity Awesome Skills.
HelloAGENTS — The orchestration kernel that makes any AI CLI smarter. Adds intelligent routing, quality verification (Ralph Loop), safety guards, and notifications.
A single-skill package for generating harness blueprints for agentic systems.
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
Mission Planner, Agent Creator, Skill Creator, and Librarian — the complete Forge suite for science-backed AI team assembly
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
MCP gateway that lets any web app expose typed actions to Claude over WebSocket — no browser automation. Pair with @tesseron/web (or /server, /react) in your app.
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability.
Think of it like building AI applications with LEGO blocks - each component (agent, tool, context provider) is:
Built on Instructor and Pydantic, it enables you to create AI applications with the same software engineering principles you already know and love.
NEW: Join our community on Discord at discord.gg/J3W9b5AZJR and our official subreddit at /r/AtomicAgents!
To install Atomic Agents, you can use pip:
pip install atomic-agents
Make sure you also install the provider you want to use. Provider SDKs are available as instructor extras:
pip install instructor[groq] # for Groq
pip install instructor[anthropic] # for Anthropic
pip install instructor[google-genai] # for Gemini
OpenAI is included by default. For a full list of supported providers, see the Instructor docs.
This also installs the CLI Atomic Assembler, which can be used to download Tools (and soon also Agents and Pipelines).
Here's a quick snippet demonstrating how easy it is to create a powerful agent with Atomic Agents:
from pydantic import Field
from openai import OpenAI
import instructor
from atomic_agents import AtomicAgent, AgentConfig, BasicChatInputSchema, BaseIOSchema
from atomic_agents.context import SystemPromptGenerator, ChatHistory