equinor/neqsim/paperlab-notebook-regression-baselines

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Define notebook baseline, tolerance, and stale-figure rules for PaperLab computational books. Use when notebooks generate figures, tables, or numeric claims that must remain stable as NeqSim and dependencies evolve.

Install

npx vskill@latest install equinor/neqsim/paperlab-notebook-regression-baselines

SKILL.md

PaperLab Notebook Regression Baselines

When to Use

USE WHEN: a book has notebooks whose outputs support chapter figures, tables, worked examples, or quantitative claims.

Pair with:

  • neqsim-notebook-patterns for notebook execution structure,
  • neqsim-regression-baselines for numerical drift principles,
  • paperlab-scientific-traceability-audit for claim provenance.

Baseline Types

TypeExampleTolerance Pattern
scalarpressure drop, NPV, water dew pointabsolute + relative tolerance
tablestream table, sensitivity outputper-column tolerance
figuregenerated PNG pathexistence + freshness + optional hash
environmentNeqSim version, Python package listrecorded metadata
claimchapter number tied to notebook outputtext-value match tolerance

Classification

  • pass: outputs are within tolerance and figures are fresh.
  • stale: notebook likely runs, but figure or claim output is outdated.
  • broken: execution or import fails.
  • missing-baseline: notebook has important outputs but no baseline yet.
  • expensive-skip: execution is known expensive and requires manual review.

Output Schema

json
{
"notebook": "chapters/ch10/notebooks/ch10_s02_teg_contactor.ipynb",
"status": "pass",
"engine": "neqsim_dev_setup",
"baselines": [
{
"name": "dry_gas_water_ppm",
"value": 32.4,
"unit": "ppm",
"abs_tol": 0.5,
"rel_tol": 0.02
}
],
"figures": [
{"path": "figures/ch10_teg_sensitivity.png", "status": "fresh"}
]
}

Safety Rules

  • Do not overwrite accepted baselines without explicit approval.
  • Record environment metadata whenever execution occurs.
  • Prefer stable engineering outputs over fragile full-notebook diffs.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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