Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 15:30 UTC

equinor / fmu-tools

fmu-tools is a library containing tools for pre- and post-processing in a Fast Model Update (FMU) context

Python · OpenEdge ABLLGPL-3.0★ 14 stars⑂ 21 forkssince Mar 2020View on GitHub ↗
KindLibraryCommand-line toolhow this is determined

equinor/fmu-tools holds a health index of 96 out of 100, placing it in the Exceptional band. It scores highest on Vitality (95/100) and lowest on AI Readiness (52/100). It was last updated today. 3 contributors account for most of its recent work.

96
overall / 100
Exceptional

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

96
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 83 is calibrated to 96 on the published index scale (record calibration 2026-08-02).

Ownership

EquinorOrganization · verified domain
1,806 followers755 public repossince Dec 2010

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIfmu-tools1.33.06,3314033 days agoenergysubsurfacereservoirscientificengineering

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

95Exceptional · 21% of overall

Development activity

92Excellent
How it's scored
36/36Push recency — last push 0 days ago
28.4/36Commit cadence — 41/52 weeks with commits
18/18Commit volume — 131 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year131
human_commit_share0.67
days_since_last_push0
active_weeks_last_year41

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 53 releases published
36/36Release recency — latest release 33 days ago
27/27Release cadence — a release every ~30.3 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count53
latest_release_tag1.33.0
releases_from_tagsno
days_since_latest_release33
mean_days_between_releases30.3
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

57Moderate · 17% of overall

Popularity & adoption

35Weak
How it's scored
18.1/60Stars — 14 stars
10.8/25Forks — 21 forks
6.4/15Watchers — 15 watchers
Inputs used
forks21
stars14
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (LGPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

63Moderate
How it's scored
50.7/80Monthly downloads — 6,331 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesfmu-tools
dependents—
ecosystemspypi
total_downloads—
monthly_downloads6,331
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

88Excellent · 23% of overall

Maintainer resilience (bus factor)

73Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
17.7/22.5Commit distribution — top contributor authored 22% of commits
13.5/13.5Contributor breadth — 19 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor3
contributors_sampled19
top_contributor_share0.215

Issue & PR responsiveness

88Excellent
How it's scored
35.6/42Issue resolution — 85% of issues closed
26.2/30PR acceptance — 295/338 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Inputs used
merged_prs295
open_issues24
closed_issues134
prs_merged_7d0
prs_decided_7d0
prs_merged_30d3
prs_decided_30d3
issue_closed_ratio0.848
closed_unmerged_prs43
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

98Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
23.4/25Owner reach — 1,806 followers of equinor
25/25Track record — 755 public repos, account ~15 yr old
Inputs used
followers1,806
owner_typeOrganization
is_verifiedyes
owner_loginequinor
public_repos755
account_age_days5,750

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 33 days ago
20/20Version history — 40 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesfmu-tools
ecosystemspypi
any_deprecatedno
min_days_since_publish33

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://equinor.github.io/fmu-tools/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://equinor.github.io/fmu-tools/
docs_sitehttps://equinor.github.io/fmu-tools/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

89Excellent · 16% of overall

Security posture

86Excellent
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
6.8/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate8.6
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages51
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:fmu-tools@1.33.0 runtime dependency closure — what installing the published package pulls in — 51 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

52Moderate · 4% of overall

Agent context & guidance

18Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
17.5/40Legible commit history — 22 of 67 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.328
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

66Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — mypy.ini
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 33 of the last 100 commits are automated dependency updates
4/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configsmypy.ini
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.33

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (mypy.ini)
54.3/55Manageable file sizes — 1/84 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes74,386
source_files_sampled84
oversized_source_files1

Key facts

14GitHub stars
19contributors
131commits, last 12 months
0days since last push
53releases
3bus factor
24open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 21 ⇿
0Stars
21Forks
49Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

048121620242122020-062023-082026-09
Major 0Minor 32Patch 15

Each point covers 6 days.

OpenSSF Scorecard 8.6 / 10
8.6aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-13 15:29 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 11 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
9Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 10
RegistryPackageVersion constraintManifest
PyPIdisjoint-set—pyproject.toml
PyPIjsonschema>=3.2.0pyproject.toml
PyPInumpy>=1.23.5pyproject.toml
PyPIopenpyxl>=2.6pyproject.toml
PyPIpandas>=0.21pyproject.toml
PyPIpydantic—pyproject.toml
PyPIpyyaml>=5.3pyproject.toml
PyPIscipy>=1.2pyproject.toml
PyPIxlrd>=1.2pyproject.toml
PyPIxtgeo>=4.23.0pyproject.toml
All dependencies 103

Full resolved dependency set from the GitHub dependency graph: 12 direct and 91 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdisjoint-set0.9.0direct
PyPIjsonschema4.26.0direct
PyPInumpy2.4.6direct
PyPInumpy2.5.2direct
PyPIopenpyxl3.1.5direct
PyPIpandas3.0.5direct
PyPIpydantic2.13.5direct
PyPIpyyaml6.0.3direct
PyPIscipy1.17.1direct
PyPIscipy1.18.1direct
PyPIxlrd2.0.2direct
PyPIxtgeo4.25.1direct
PyPIalabaster1.0.0indirect
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIast-serialize0.8.0indirect
PyPIattrs26.1.0indirect
PyPIautoapi2.0.1indirect
PyPIbabel2.18.0indirect
PyPIcertifi2026.7.22indirect
PyPIcharset-normalizer3.5.1indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.3indirect
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PyPIcycler0.12.1indirect
PyPIdeprecation2.1.0indirect
PyPIdocutils0.21.2indirect
PyPIemcee3.1.6indirect
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PyPIexecnet2.1.2indirect
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PyPIhdf5plugin7.0.0indirect
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PyPIimagesize2.0.1indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIjoblib1.5.3indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIkiwisolver1.5.1indirect
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PyPImarkdown-it-py4.2.0indirect
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PyPImypy2.3.1indirect
PyPImypy-extensions1.1.0indirect
PyPImyst-parser5.1.0indirect
PyPIpackaging26.3indirect
PyPIpathspec1.1.1indirect
PyPIpillow12.3.0indirect
PyPIpluggy1.6.0indirect
PyPIpyarrow25.0.1indirect
PyPIpydantic-core2.46.5indirect
PyPIpyevtk1.7.0indirect
PyPIpygments2.21.0indirect
PyPIpyparsing3.3.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
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PyPIpytest-runner6.0.1indirect
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PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIresfo5.0.1indirect
PyPIrich15.0.0indirect
PyPIroffio1.1.1indirect
PyPIrpds-py2026.6.3indirect
PyPIrstcheck6.3.0indirect
PyPIrstcheck-core1.3.2indirect
PyPIruff0.16.5indirect
PyPIsegyio1.9.14indirect
PyPIshapely2.1.2indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsphinx8.1.3indirect
PyPIsphinx-argparse0.6.1indirect
PyPIsphinx-autodoc-typehints2.3.0indirect
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PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jquery4.1indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPItomli2.4.1indirect
PyPItyper0.27.2indirect
PyPItypes-pyyaml6.0.12.20260815indirect
PyPItyping-extensions4.16.0indirect
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Dependency advisories 0

Installing pypi:fmu-tools@1.33.0 pulls in 51 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.