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framework

framework is a skill for Claude Code from Eigenwise/atomic-agents. It costs 74 tokens per session (2,258 once invoked), scanned A, original, MIT.

A reference guide for Atomic Agents, a Python framework for building language-model applications with structured, validated data. It explains agents, tools, prompts, conversation history, context providers, and provider setup.

In plain words
What is it for?
Use it when building or configuring Atomic Agents applications, connecting language-model providers, designing schemas, or coordinating multiple agents and tools.
Why use it?
It gives one place to understand how the framework's parts connect, instead of having to piece together separate concepts and configuration details.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the atomic-agents plugin — 7 skills, 2 agents shipped together

not rated 6.3krepo +5 8d ago A scan SkillSpector: pass 74 tokens original MIT

Good fit Use it when building or configuring Atomic Agents applications, connecting language-model providers, designing schemas, or coordinating multiple agents and tools.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eigenwise/atomic-agents/framework
View source ↗ Eigenwise/atomic-agents eigenwise.github.io
About the project

Atomic Agents is a lightweight, modular framework for assembling AI agents and applications from single-purpose components such as agents, tools, and context providers. It is for developers building maintainable agentic AI pipelines with reusable, composable parts and structured outputs. The catalogue entries provide agent skills, instructions, settings, and related development workflows for the framework.

Eigenwise/atomic-agents · 6,319 stars · on GitHub · eigenwise.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Eigenwise/atomic-agents --skill framework
Clone the repo
git clone --depth 1 https://github.com/Eigenwise/atomic-agents

Made for: Claude Code.

Or install atomic-agents, the plugin that ships this one along with the rest of its 7 skills, 2 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for framework

README.md
[![agentmods](https://agentmods.dev/badge/skills/eigenwise/atomic-agents/framework/github.svg)](https://agentmods.dev/skills/eigenwise/atomic-agents/framework)
Your own site
<a href="https://agentmods.dev/skills/eigenwise/atomic-agents/framework"><img src="https://agentmods.dev/badge/skills/eigenwise/atomic-agents/framework/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for framework

Your own site · 80×15
<a href="https://agentmods.dev/skills/eigenwise/atomic-agents/framework"><img src="https://agentmods.dev/badge/skills/eigenwise/atomic-agents/framework.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,258 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.02258
Opus 5.5 $0.00030 $0.00903
Sonnet 5.5 $0.00015 $0.00452
Haiku 4.5 $0.00007 $0.00226

Measured 2mo ago against content hash 79dc389da4f8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

framework scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

claude-plugin/atomic-agents/skills/framework/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Atomic 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
History ChatHistory Conversation state, serializable, token-counted
Tool BaseTool[In, Out] Deterministic capability the agent can invoke
Context BaseDynamicContextProvider Dynamic section injected into the system prompt at runtime

All communication between these uses BaseIOSchema subclasses with docstring-required descriptions.

Canonical imports

from atomic_agents import (
    AtomicAgent, AgentConfig,
    BasicChatInputSchema, BasicChatOutputSchema,
    BaseIOSchema, BaseTool, BaseToolConfig,
)
from atomic_agents.context import (
    ChatHistory, Message,
    SystemPromptGenerator, BaseDynamicContextProvider,
)
# Optional: MCP interop
from atomic_agents.connectors.mcp import fetch_mcp_tools, MCPTransportType

Do not use legacy paths like atomic_agents.lib.base.* or atomic_agents.agents.base_agent — those were retired. Import from the top-level package where possible.

Minimum viable agent

import os, instructor, openai
from atomic_agents import AtomicAgent, AgentConfig, BasicChatInputSchema, BasicChatOutputSchema
from atomic_agents.context import ChatHistory

client = instructor.from_openai(openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"]))

agent = AtomicAgent[BasicChatInputSchema, BasicChatOutputSchema](
    config=AgentConfig(
        client=client,
        model="gpt-5-mini",
        history=ChatHistory(),
    )
)

reply = agent.run(BasicChatInputSchema(chat_message="Hello"))
print(reply.chat_message)

Read the full file on GitHub · 156 lines

Files

What ships with it

11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 156 lines · 74 tokens per session scan A 79dc389da4f8

Subscribe to this mod's changes

framework is a skill published in the GitHub repository Eigenwise/atomic-agents (6,319 stars, last pushed 8d ago), licensed MIT. It adds 74 tokens to every session and 2,258 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Building agentsaiartificial-intelligencelarge-language-modellarge-language-modelsllmsopenai
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framework next to 6 skills from other repositories
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