embodiment-card 0.1.2

Validate and render robot embodiment metadata for dataset and VLA release review.

embodiment-card

embodiment-card validates and renders structured robot embodiment metadata for dataset and vision-language-action release review.

At a Glance

Job	Make robot hardware, sensing, action, frame, control, environment, and limitation assumptions reviewable.
Built for	Robotics dataset curators, VLA researchers, release reviewers, and documentation owners.
Differentiator	Dependency-free schema validation plus Markdown and Hugging Face README rendering.
Produces	A validated JSON card or a human-readable embodiment card for release documentation.

Install

python -m pip install "embodiment-card==0.1.2"

Verified Quickstart

Run from a source checkout:

embodiment-card validate examples/mock_so101_card.json

embodiment-card render examples/mock_so101_card.json \
  --hf-readme \
  --out /tmp/SO101-EMBODIMENT.md

The bundled SO-101 fixture validates and renders Hugging Face-compatible YAML tags followed by an embodiment card.

Required Disclosure

The v1 card requires:

• name and robot morphology;
• at least one sensor;
• action-space metadata;
• at least one coordinate frame;
• positive control rate;
• teleoperation method;
• environment assumptions;
• safety boundaries and known limitations.

Validation checks required fields and a small set of structural constraints. It does not verify hardware, calibration, units, coordinate transforms, or the truth of a disclosure.

Runtime, Data, and Network Boundary

• The CLI reads one local JSON file and writes Markdown to a file or stdout.
• It does not inspect robot media, connect to hardware, contact Hugging Face, or make network requests.
• --hf-readme formats local text only; it does not create or update a Hub repository.
• No redaction is applied. Review cards for private paths, operators, sites, or hardware identifiers before sharing them.

Limitations

• Validation covers required fields and simple structure only. It does not check calibration, coordinate transforms, units, or hardware truth.
• Rendered cards remain self-reported documentation, not a safety review, hardware certification, or deployment approval.

Compatibility

robostudio-engine exposes a direct robostudio card integration that imports embodiment-card when the package is installed or available in the AuraOne monorepo. The standalone card format can also be embedded in any dataset or model README.

Publication Status

Verified on 2026-07-13:

• PyPI: embodiment-card==0.1.2
• GitHub release: v0.1.2
• Bundled cards describe mock tutorial datasets and do not establish hardware validation or safety assurance.

Next Action

Fill a card from one real dataset's reviewed metadata, have the hardware owner verify frames and control rate, then publish the rendered disclosure beside the dataset.