Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 12:56 UTC

cnpem / AtomPacker

A python package for packing nanoclusters into supramolecular cages.

PythonGPL-3.0★ 2 stars⑂ 0 forkssince Sep 2023View on GitHub ↗

cnpem/AtomPacker holds a health index of 59 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (81/100) and lowest on Community & Adoption (24/100). It was last updated 7 days ago. A single contributor accounts for most of its recent work.

59
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.

59
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 56 is calibrated to 59 on the published index scale (record calibration 2026-08-02).

Ownership

95 followers82 public repossince Apr 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIAtomPacker0.6.0-1550 days agocomputational-chemistryatom-packingsphere-packing

Metrics by category

Vitality

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

74Good · 21% of overall
How it's scored
36/36Push recencylast push 7 days ago
5.5/36Commit cadence8/52 weeks with commits
14.6/18Commit volume41 commits in the last year
0/10OpenSSF Scorecard: Maintained1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year41
human_commit_share
days_since_last_push7
active_weeks_last_year8

Release discipline

100Exceptional
How it's scored
27/27Ships releases16 releases published
36/36Release recencylatest release 50 days ago
27/27Release cadencea release every ~32.5 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count16
latest_release_tag0.6.0
releases_from_tagsno
days_since_latest_release50
mean_days_between_releases32.5
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?

24At Risk · 17% of overall
How it's scored
0/60Stars2 stars
0/25Forks0 forks
0/15Watchers2 watchers
Inputs used
forks0
stars2
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (GPL-3.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

54Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
3.7/22.5Commit distributiontop contributor authored 84% of commits
2.7/13.5Contributor breadth2 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.836
How it's scored
0/42Issue resolutionno issues or no data
12.4/30PR acceptance33/80 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/29 approved changesets -- score normalized to 0
Inputs used
merged_prs33
open_issues0
closed_issues0
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio
closed_unmerged_prs47
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
14.3/25Owner reach95 followers of cnpem
19.5/25Track record82 public repos, account ~3 yr old
Inputs used
followers95
owner_typeOrganization
is_verified
owner_logincnpem
public_repos82
account_age_days1,184
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 50 days ago
20/20Version history15 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesAtomPacker
ecosystemspypi
any_deprecatedno
min_days_since_publish50

Engineering Quality

Are baseline engineering and documentation practices in place?

81Excellent · 19% of overall
How it's scored
24/24CI workflows3 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests1 out of 1 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://cnpem.github.io/AtomPacker/
10/10Repository description
10/10Topics6 topics
10/10Wiki
Inputs used
topicssupramolecular-cages, atom-packing, modeling, nanoclusters, nanoparticles, python-package
has_wikiyes
homepagehttps://cnpem.github.io/AtomPacker/
docs_sitehttps://cnpem.github.io/AtomPacker/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

46Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.5/2.5CI-Tests1 out of 1 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/29 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packagingpackaging workflow detected
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
0/5Security-Policysecurity policy file not 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_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

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.

34At Risk · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/28 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes34,560
source_files_sampled28
oversized_source_files0

Key facts

2GitHub stars
2contributors
41commits, last 12 months
7days since last push
16releases
1bus factor
0open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.6 / 10
4.6aggregate

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 · 2026-07-17 12:56 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests1 out of 1 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/29 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPIase>=3.28.0,<4.0.0pyproject.toml
PyPIbiopython>=1.7.0pyproject.toml
PyPIMDAnalysis>=2.9.0,<3.0.0pyproject.toml
PyPInumpy>=2.0.0,<2.5.0pyproject.toml
PyPIpandas>=2.3.0,<3.1.0pyproject.toml
PyPIplotly>=6.0.0,<6.8.0pyproject.toml
PyPIpyKVFinder>=0.9.0,<1.0.0pyproject.toml
PyPIscikit-learn>=1.7.0,<2.0.0pyproject.toml
PyPItqdm>=4.67.0pyproject.toml
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 9 direct and 7 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIasedirect
PyPIbiopythondirect
PyPImdanalysisdirect
PyPInumpydirect
PyPIpandasdirect
PyPIplotlydirect
PyPIpykvfinderdirect
PyPIscikit-learndirect
PyPItqdmdirect
PyPIblackindirect
PyPIflake8indirect
PyPIpytestindirect
PyPIsetuptoolsindirect
PyPIsphinxindirect
PyPIsphinx-rtd-themeindirect
PyPIwheelindirect
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 v0.11.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.