framework
SkillGuide for the Atomic Agents Python framework — schemas, agents, tools, context providers, prompts, orchestration, and provider configuration. Use when code imports from `atomic_agents`, defines an `AtomicAgent`, `BaseTool`, or `BaseIOSchema`, or the user asks about multi-agent orchestration or LLM-p
Install
git clone https://github.com/BrainBlend-AI/atomic-agents.git ~/.claude/skills/frameworkWhat is framework?
Guide for the Atomic Agents Python framework — schemas, agents, tools, context providers, prompts, orchestration, and provider configuration. Use when code imports from `atomic_agents`, defines an `AtomicAgent`, `BaseTool`, or `BaseIOSchema`, or the user asks about multi-agent orchestration or LLM-provider wiring in an atomic-agents project.
What this can do
Capabilities declared in this component's own frontmatter — not inferred.
Inherit all session tools
Declares no tool restrictions — inherits every session tool
~86 tokens of context used while enabled, before you invoke anything
Trust
91/100 · Excellent2 factors scored below maximum
Documentation
README · ~6 min readAtomic Agents Framework
Atomic Agents is a lightweight Python framework for building LLM applications with typed, structured input and output. It layers on top of Instructor and Pydantic so every interaction between user, agent, tool, and context is a validated schema.
This skill orients Claude on the framework and routes to focused reference files as the task requires.
Core abstractions
| Concept | Class | Role |
|---|---|---|
| Schema | BaseIOSchema | Typed input/output contract — every agent/tool I/O is one |
| Agent | AtomicAgent[In, Out] | LLM-backed transformer from input schema to output schema |
| Config | AgentConfig | Wires client, model, history, prompt, roles, API params |
| Prompt | SystemPromptGenerator | Three-section prompt: background, steps, output_instructions |
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