new-app

A project starter for creating a new Atomic Agents application from scratch. Atomic Agents is a Python framework for building language-model applications with typed inputs and outputs.

In plain words
What is it for?
Use it when starting a new Atomic Agents project and you need a basic Python application that can run immediately.
Why use it?
It removes the repetitive setup work of creating the project structure, dependency configuration, first agent, schemas, client, and runnable entry point.

Skill for Claude CodeCodex

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

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.

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

Made for: Claude Code, Codex.

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

Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,981 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00076 $0.01981
Opus 5 $0.00038 $0.00991
Sonnet 5 $0.00015 $0.00396
Haiku 4.5 $0.00008 $0.00198

Measured 3d ago against content hash a425bb1fa43d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

new-app 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 3d 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/new-app/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

New Atomic Agents Project

Scaffold a fresh Atomic Agents project. The result is a single-package Python project with one working agent, one schema pair, a provider-wrapped client, and a runnable main.py.

This skill is opinionated. Produce a complete, tested skeleton the user can run immediately.

Phase 1 — Interrogate

Ask these questions in one message, not one-at-a-time. Skip any the user already answered (including via $ARGUMENTS).

  1. Project name — used as both directory name and package name. Default from $ARGUMENTS if provided. Normalize to kebab-case for the directory and snake_case for the package.
  2. LLM provider — OpenAI / Anthropic / Groq / Ollama / Gemini / OpenRouter / MiniMax. Default: OpenAI.
  3. Agent type — a rough one-liner. Shapes the default SystemPromptGenerator content and the starter schema pair. Defaults to a generic chat agent.
  4. Toolinguv (default, because the repo uses uv) or pip + venv.

Do not ask about project layout, Python version, or dependency list. Pick them.

Phase 2 — Confirm the plan

State the plan in one short block and wait for a yes. Include:

  • Directory: <project-name>/
  • Package: <project_name>/
  • Python: >=3.12 (Atomic Agents uses PEP 695 generics)
  • Dependencies: atomic-agents>=2.7, instructor[<provider-extra>]>=1.14, python-dotenv, rich
  • Dev dependencies: pytest, pytest-asyncio, ruff
  • First agent: <agent-type> — uses BasicChatInputSchema/BasicChatOutputSchema unless the agent type calls for custom schemas
  • Default model for the chosen provider (see framework/references/providers.md)
  • Entry point: main.py with a REPL

Phase 3 — Scaffold

Create files in this order. Verify each step before proceeding.

Directory and package

<project-name>/
├── pyproject.toml
├── .env.example
├── .gitignore
├── README.md
├── AGENTS.md
├── CLAUDE.md
└── <project_name>/
    ├── __init__.py
    └── main.py

pyproject.toml

Use the template from framework/references/project-structure.md, substituting the chosen provider extra and project name.

Read the full file on GitHub · 171 lines

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. 3d ago First seen · 171 lines · 76 tokens per session scan A a425bb1fa43d

Subscribe to this mod's changes

new-app is a skill published in the GitHub repository Eigenwise/atomic-agents (6,218 stars, last pushed 9d ago), licensed MIT. It adds 76 tokens to every session and 1,981 once invoked, about $0.0004 per session on Opus 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.

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