uncertainty-and-units SKILL.md skillA
uncertainty-and-units from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/uncertainty-and-units@v1.3Pins v1.3 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/uncertainty-and-units/SKILL.md- Versions recorded
- 4
- Latest version
- v1.3, committed Oct 1, 2026
- First version recorded
- Jul 26, 2026
- Size
- 21,731 bytes
- Repository stars
- 56,497
- License
- MIT
Tracks physical units and propagates measurement uncertainty in scientific calculations using pint and uncertainties. Use for unit conversion and dimensional checking, GUM uncertainty budgets, Type A and Type B evaluation, coverage factors and expanded uncertainty, Monte Carlo propagation, significant-figure and plus-minus reporting, error propagation through curve fits, CODATA constants, auditing Python code for stripped units or broken uncertainty propagation, and order-of-magnitude…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Uncertainty and units ## Scope Use this skill whenever a calculation carries physical units or a reported number needs an uncertainty. Concretely: - converting between units, including conversions that need a physical context (wavelength to photon energy, mass to amount of substance, energy to temperature); - propagating uncertainty through a measurement model, with or without correlated inputs; - building a GUM uncertainty budget from calibration certificates, specifications, and repeatability data; - choosing a coverage factor and deciding whether `k = 2` is defensible; - rounding and writing a result so a reader knows what the `±` means; - extracting parameter uncertainties from a curve fit without discarding correlations; - reviewing existing analysis code for silent unit and uncertainty defects; - checking that a dimensionally consistent answer is also physically possible — the order of magnitude, the dimensionless group, and the regime it implies. This skill covers the metrology and the two libraries that implement it. It does not cover statistical inference, model selection, or study design — see `statistical-analysis`, …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/uncertainty-and-units@sha256:caaafa079a4eaac6The line at the top of this page pins the label v1.3, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_iq5euqr4w4eysfcv)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Jul 26, 2026 and Oct 1, 2026, about one every 22 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.3 latest | 2026-10-01 | a92663a | 21,731 B | A | view · diff |
| v1.2 | 2026-09-30 | ce9e6e9 | 20,066 B | A | view · diff |
| v1.1 | 2026-09-02 | 1e5eeff | 19,864 B | A | view · diff |
| v1.0 | 2026-07-26 | cca1e05 | 18,906 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (21731 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_iq5euqr4w4eysfcv GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/uncertainty-and-units GET https://markdownregistry.com/api/v1/blob/caaafa079a4eaac6012717bcf705dec0417b5434f5dbd1af934a3a36ad375722
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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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