Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 20:10 UTC

dralgroup / mlatom

AI-enhanced computational chemistry

Python · FortranApache-2.0★ 162 stars⑂ 24 forkssince Aug 2023View on GitHub ↗
KindCommand-line toolhow this is determined

dralgroup/mlatom holds a health index of 62 out of 100, placing it in the Moderate band. It scores highest on Vitality (83/100) and lowest on AI Readiness (41/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

62
overall / 100
Moderate

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.

62
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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02).

Ownership

Pavlo O. Dral & groupPersonal account
74 followers24 public repossince Feb 2022Xiamen University

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPImlatompoints to another repo — not scored3.25.51,844681 day ago

Metrics by category

Vitality

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

83Excellent · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
10.4/36Commit cadence15/52 weeks with commits
14.8/18Commit volume43 commits in the last year
10/10OpenSSF Scorecard: Maintained29 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year43
human_commit_share1
days_since_last_push1
active_weeks_last_year15

Release discipline

100Exceptional
How it's scored
27/27Ships releases46 releases published
36/36Release recencylatest release 1 days ago
27/27Release cadencea release every ~6.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count46
latest_release_tagv3.25.5
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases6.7
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?

66Good · 17% of overall
How it's scored
35.8/60Stars162 stars
11.3/25Forks24 forks
1.7/15Watchers3 watchers
Inputs used
forks24
stars162
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

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

48Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
5.5/22.5Commit distributiontop contributor authored 76% of commits
8.1/13.5Contributor breadth6 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.757
How it's scored
26.2/42Issue resolution62% of issues closed
28.6/30PR acceptance42/44 decided PRs merged
13/13Newcomer PR acceptance1/1 first-time contributors' PRs merged in 30d
1.5/15OpenSSF Scorecard: Code-ReviewFound 4/28 approved changesets -- score normalized to 1
Inputs used
merged_prs42
open_issues3
closed_issues5
prs_merged_7d1
prs_decided_7d1
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.625
closed_unmerged_prs2
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
13.5/25Owner reach74 followers of dralgroup
19.3/25Track record24 public repos, account ~4 yr old
Inputs used
followers74
owner_typeUser
is_verified
owner_logindralgroup
public_repos24
account_age_days1,669
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

44Weak · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 4 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttp://mlatom.com
10/10Repository description
10/10Topics11 topics
10/10Wiki
Inputs used
topicsartificial-intelligence, computational-chemistry, machine-learning, machine-learning-potential, quantum-chemistry, quantum-chemistry-programs, quantum-mechanics, deep-learning, kernel-method, kernel-ridge-regression, neural-network
has_wikiyes
homepagehttp://mlatom.com
docs_sitehttp://mlatom.com
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

49Weak · 16% of overall
How it's scored
3.8/7.5Binary-Artifactsbinaries present in source code
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 4 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-ReviewFound 4/28 approved changesets -- score normalized to 1
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained29 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.4
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.
How it's scored
9/35Direct dependencies free of known advisories2 affected: torch 2.7.1 (high 8.8), setuptools 80.10.2 (moderate 6.1)
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
32.8/40No advisories left outstanding1 advisory-carrying package(s) unaddressed past 90 days; oldest published 531 days ago
Inputs used
sourceosv
advisories12
affected_packages2
assessed_packages64
unassessed_packages0
affected_by_severityhigh 1, moderate 1
direct_affected_packages2
Matched the pypi:mlatom@3.25.5 runtime dependency closure — what installing the published package pulls in — 64 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.

41Weak · 4% of overall
How it's scored
45/45Agent instructionsAGENTS.md
0/15Machine-readable docs (llms.txt)
21.3/40Legible commit history40 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.4
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes2,804
How it's scored
18/18One-command bootstrapmlatom/MLatomF_src/Makefile
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesmlatom/MLatomF_src/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
49.9/55Manageable file sizes10/107 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes228,578
source_files_sampled107
oversized_source_files10

Key facts

162GitHub stars
6contributors
43commits, last 12 months
1days since last push
46releases
1bus factor
3open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'mlatom' points at a different repository (http://mlatom.com); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 24 ⇿
0Stars
24Forks
43Releases

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.

048121620242422024-032025-062026-09
Major 0Minor 24Patch 19

Each point covers 3 days.

OpenSSF Scorecard 4.4 / 10
4.4aggregate

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 20:10 UTC

5Binary-Artifactsbinaries present in source code
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
0CI-Tests0 out of 4 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 4/28 approved changesets -- score normalized to 1
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained29 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 16
RegistryPackageVersion constraintManifest
PyPInumpy<2pyproject.toml
PyPIscipypyproject.toml
PyPIh5pypyproject.toml
PyPIpyh5mdpyproject.toml
PyPItorch>=2.1.2,<2.8pyproject.toml
PyPItorchani>=2.2.3,<2.3pyproject.toml
PyPIsetuptools<81pyproject.toml
PyPImatplotlibpyproject.toml
PyPIstatsmodelspyproject.toml
PyPItqdmpyproject.toml
PyPIjoblibpyproject.toml
PyPIrequestspyproject.toml
PyPIpsutilpyproject.toml
PyPIgeometric<1.1.1pyproject.toml
PyPIrmsdpyproject.toml
PyPIfortranformatpyproject.toml
All dependencies 5

Full resolved dependency set from the GitHub dependency graph: 5 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIgeometricdirect
PyPInumpydirect
PyPIsetuptoolsdirect
PyPItorchdirect
PyPItorchanidirect
Dependency advisories 2

Installing pypi:mlatom@3.25.5 pulls in 64 packages, direct and transitive: 2 carry known advisories, of which 2 are direct dependencies.

PackageVersionRelationSeverityAdvisoriesFixed in
torch2.7.1directhigh102.13.0
setuptools80.10.2directmoderate283.0.0

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.

The message is kept through sign-in.

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 statisticsPyPI.