nenadzaric/skills-intel-unit-uncertainty-audit repository overview

⁠unit-uncertainty-audit

Statically audit Python source for silent unit and measurement-uncertainty mistakes (stripped units, offset temperatures, population vs sample standard deviation, broken propagation, hard-coded CODATA constants) with K-Dense's audit_units. JSON findings; code is parsed, never run.

⁠Immutable image

docker pull --platform linux/amd64 docker.io/nenadzaric/skills-intel-unit-uncertainty-audit@sha256:1460ffc0923b9a295e52ecb8e537c2477c09708019a327733e6b6b01c62c45ce

Image index: sha256:02ed2bf2cf050162c17b6abc47918b82a987826651e8a882ecc5e572e9564d50.

⁠Source and license notices

This accompanying OCI artifact contains the original build recipe and runtime sources, pinned source directions, and original installed license/notices. Registry relocation and source-link metadata corrections in the current Git recipe do not change the image executable bytes. It is not a full mirror of every upstream source archive.

oras pull docker.io/nenadzaric/skills-intel-unit-uncertainty-audit@sha256:69db0c6366ece512ccb3fb7e831caf9ec77ca61a4fb57f1953c9f5214b4e1e97
sha256sum unit-uncertainty-audit-source-notices.tar.gz

Expected bundle SHA256: 0167823942bb43a820f7ea27218f04fbc45472fe7a26eeddc6fc46f7b02702c7. Extract to read build-source/ and notices/SOURCE-AND-NOTICES.json.

Native license: MIT.

Pinned source archive: https://codeload.github.com/k-dense-ai/scientific-agent-skills/tar.gz/065b734670d7d990627dbc06a05b5a99be33f1f1⁠