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.
npx agentmods add skills/eigenwise/atomic-agents/create-atomic-toolnpx skills add Eigenwise/atomic-agents --skill create-atomic-toolgit clone --depth 1 https://github.com/Eigenwise/atomic-agentsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00099 | $0.02141 |
| Opus 5 | $0.00049 | $0.01071 |
| Sonnet 5 | $0.00020 | $0.00428 |
| Haiku 4.5 | $0.00010 | $0.00214 |
Grade A, and why
create-atomic-tool 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create an Atomic Agents Tool
A tool is a deterministic capability an agent can invoke. In Atomic Agents, every tool is a BaseTool[InSchema, OutSchema] subclass with a typed run() (and optional run_async()). The input/output schemas double as the tool's signature for the LLM and as Pydantic validation at runtime.
For deep material (MCP interop, distributing as a standalone package, advanced error patterns), the authority is ../framework/references/tools.md. This skill is the action-oriented path: clarify → write → verify.
When this fires vs the umbrella framework skill
- This skill: the user is creating a specific tool — wrapping an API, building a calculator, scraping a page, querying a DB.
frameworkskill: questions about Atomic Agents in general, or the user is doing something other than authoring a tool.
Phase 1 — Clarify
Bundle into one message:
- What does the tool do? One sentence. This becomes the class docstring and feeds the LLM's tool description.
- Inputs and outputs. Names, types, units. If unclear, propose a schema pair and confirm.
- External dependencies. HTTP API? DB? Local computation only? If HTTP, what auth (API key env var, OAuth, none)?
- Sync, async, or both? If the rest of the project is async or the call is I/O bound, plan a
run_async()alongsiderun(). - Failure modes. Rate limits, not-found, network errors — how should the agent see them? Default: typed failure output, not raised exceptions.
Skip any question already answered in context.
Phase 2 — Plan
Confirm the location and shape in one short block, then proceed:
- File:
<project>/tools/<tool_name>_tool.py(in-project tool — see../framework/references/project-structure.md). - Schemas:
<ToolName>Input,<ToolName>Output, optionally a typed failure shape. - Config:
<ToolName>Config(BaseToolConfig)if the tool needs API keys, base URLs, timeouts, retries. - Sync vs async: pick one or both.
- Error pattern: typed failure output (preferred) vs raise (only for programmer error).
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.
- 2d ago First seen · 201 lines · 99 tokens per session scan A b5c47926e2e1
create-atomic-tool is a skill published in the GitHub repository Eigenwise/atomic-agents (6,218 stars, last pushed 9d ago), licensed MIT. It adds 99 tokens to every session and 2,141 once invoked, about $0.0005 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.
Other skills, from other repositories
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
auto
Autonomous pipeline: claim → experiment (mechanism routing folded in) → verify → iteration. Each stage is delegated to an isolated agent with its own context window and configurable model. Gates are AUTOPROCEED-governed; defaults run end-to-end without human input. Use when user says "auto pipeline", or wants the core…
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
mcp-apps-builder
MANDATORY for ALL MCP server work - mcp-use framework best practices and patterns. READ THIS FIRST before any MCP server work, including: Creating new MCP servers Modifying existing MCP servers (adding/updating tools, resources, prompts, widgets) Debugging MCP server issues or errors Reviewing MCP server code for…
skill-creator
Create, install, or update skills in the workspace. Use when (1) installing a skill from a URL or remote source, (2) creating a new skill from scratch, (3) updating or restructuring existing skills. Always use this skill for any skill installation or creation task.
make_plan
For external plan request scenarios, guides the Agent to request a clear, actionable, step-by-step plan from a stronger Agent via listagents and chatwithagent, emphasizing that the plan is executed by the requester, not by the consulted Agent.