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-schemanpx skills add Eigenwise/atomic-agents --skill create-atomic-schemagit 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 | $0.00089 | $0.01492 |
| Opus 5 | $0.00044 | $0.00746 |
| Sonnet 5 | $0.00018 | $0.00298 |
| Haiku 4.5 | $0.00009 | $0.00149 |
Grade A, and why
create-atomic-schema 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 yesterday.
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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create an Atomic Agents Schema
Author a BaseIOSchema pair (input and/or output) that becomes the contract between an agent or tool and its caller. The framework enforces docstrings on every subclass, and Instructor flows field descriptions into the LLM prompt — so the schema is part of the prompt, not just typing.
For deep material (validators, discriminated unions, error envelopes), the authority is ../framework/references/schemas.md. This skill is the action-oriented path: clarify → write → validate.
When this fires vs the umbrella framework skill
- This skill: the user is creating or modifying a specific schema — e.g. "design the output schema for the planner agent", "add a field to
WeatherInput", "split the result into success and failure variants". frameworkskill: the user is asking about Atomic Agents in general or doing something other than authoring schemas.
Phase 1 — Clarify
Ask only what is not already obvious from context. Bundle into one message; do not interrogate one-at-a-time.
- Caller — is this for an
AtomicAgent, aBaseTool, both (an agent that emits a tool-input schema), or a nested sub-schema? - Direction — input only, output only, or a paired Input/Output?
- Fields — what fields does the caller need, with which types? (Required vs optional, defaults, constraints.)
- Failure modes — can this legitimately fail? If yes, plan a typed error variant rather than raising. See
../framework/references/schemas.md→ "Error-schema pattern".
If the user is mid-conversation about an existing schema, skip questions answered in context.
Phase 2 — Write
Place schema(s) where they will be imported from. Conventional locations:
<project>/agents/<agent_name>/schemas.py— agent-owned schemas<project>/tools/<tool_name>_tool.py— tool I/O lives next to the tool<project>/schemas/<topic>.py— schemas shared across multiple components
Required ingredients on every schema
- Subclass
BaseIOSchema(notBaseModel). - A non-empty class docstring — the framework raises at import otherwise. Write it for the LLM, because Instructor uses it as the schema's
description. - Every
Field(...)carries adescription=written for the LLM. - Use
Literal[...]for closed sets before reaching forEnum— flatter JSON Schema, easier for Instructor.
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.
- yesterday First seen · 138 lines · 89 tokens per session scan A f4a77c1e6101
create-atomic-schema is a skill published in the GitHub repository Eigenwise/atomic-agents (6,213 stars, last pushed 8d ago), licensed MIT. It adds 89 tokens to every session and 1,492 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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