rio
Rio is a fully autonomous, one-shot coding agent built on SKILL.state: Scalable Long-Horizon Agent Skills. It has no interactive terminal UI, no conversation history, and no follow-up turns. Start a task, let it run, and Rio exits only when the task completes or aborts.
Each model step receives the fixed skill instructions, current JSON execution
state, and the result of the previous action. The task is stored in the
initial state's goal field; it is never treated as a user observation.
Reasoning and prior messages are not replayed.
Use
uv sync
uv run rio "Inspect this project and fix the parser"
uv run rio task.md
The normal workflow is to write the task in a Markdown file, then run Rio
against it. A sole *.md argument is loaded as the task:
uv run rio feature.md
You can add a short instruction when invoking it:
uv run rio "Follow feature.md, run the tests, and finish the implementation"
Use --provider NAME --model MODEL to choose a configured provider and
--approve to allow project instructions and extensions for that run. Rio
renders committed actions, state changes, retries, and the final result with
Rich.
Development
uv run pytest
uv run ruff check .
rio.ai is a multi-provider LLM streaming SDK. rio.agent is the
SKILL.state runtime, and rio.coding supplies the autonomous coding skill and
tools. rio.cli is the public one-shot command-line entry point.
1 maintainer
Release files for rio 0.4.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rio-0.4.4.tar.gz | 454.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rio-0.4.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 844.0 kB
Release files / rio-0.4.4.tar.gz
| Download URL | rio-0.4.4.tar.gz |
|---|---|
| Size | 454.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / rio-0.4.4-py3-none-any.whl
| Download URL | rio-0.4.4-py3-none-any.whl |
|---|---|
| Size | 389.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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