Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-25 15:52 UTC

puzl-cloud / kube-models

Python dataclasses for all Kubernetes built-in resources (v1.23+)

PythonMIT★ 4 stars⑂ 0 forkssince Nov 2025View on GitHub ↗

puzl-cloud/kube-models holds a health index of 28 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (39/100) and lowest on Security (27/100). It was last updated today. A single contributor accounts for most of its recent work.

28
overall / 100
At Risk

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.

28
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 34 is calibrated to 28 on the published index scale (record calibration 2026-08-02).

Ownership

puzl.cloudOrganization
12 followers18 public repossince Jan 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIkube-models0.6.04,013110 days agokuberneteskubesdkmodels

Metrics by category

Vitality

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

30At Risk · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
4.2/36Commit cadence — 6/52 weeks with commits
9.7/18Commit volume — 11 commits in the last year
0/10OpenSSF Scorecard: Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year11
human_commit_share—
days_since_last_push0
active_weeks_last_year6
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count0
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?

36Weak · 17% of overall
How it's scored
7.7/60Stars — 4 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars4
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
48/80Monthly downloads — 4,013 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageskube-models
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,013
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?

39Weak · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1.9/22.5Commit distribution — top contributor authored 92% of commits
2.7/13.5Contributor breadth — 2 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.917
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — no decided pull requests or no data
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/12 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
8/25Owner reach — 12 followers of puzl-cloud
21.3/25Track record — 18 public repos, account ~6 yr old
Inputs used
followers12
owner_typeOrganization
is_verifiedno
owner_loginpuzl-cloud
public_repos18
account_age_days2,433

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 11 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageskube-models
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

38Weak · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsdataclasses, kubernetes, python, k8s
has_wikino
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

27At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/12 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — no data
0/5Pinned-Dependencies — no data
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate2.7
Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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.

36Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no 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
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
11/11Static type checking — py.typed
0/10Reproducible environment
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configspy.typed
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance, OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
27/45Type-checkable code — Python with type-check config (py.typed)
54.9/55Manageable file sizes — 1/1,042 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes72,703
source_files_sampled1,042
oversized_source_files1

Key facts

4GitHub stars
2contributors
11commits, last 12 months
0days since last push
0releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:kube-models@0.6.0; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 2.7 / 10
2.7aggregate

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 · 2026-09-25 15:52 UTC

10Binary-Artifactsno binaries found in the repo
1Branch-Protectionbranch protection is not maximal on development and all release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/12 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update 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
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

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 statistics — PyPI.