Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-26 09:36 UTC

Oxid15 / cascade

Small-scale MLOps library

PythonApache-2.0★ 21 stars⑂ 1 forksince Feb 2022View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

Oxid15/cascade holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Vitality (81/100) and lowest on AI Readiness (37/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

69
overall / 100
Good

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.

69
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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

Ilia MoiseevPersonal account
12 followers21 public repossince Sep 2017

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
PyPIcascade-ml0.18.03733114 days ago

Metrics by category

Vitality

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

81Excellent · 21% of overall
How it's scored
36/36Push recency — last push 2 days ago
9/36Commit cadence — 13/52 weeks with commits
18/18Commit volume — 233 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year233
human_commit_share1
days_since_last_push2
active_weeks_last_year13
How it's scored
27/27Ships releases — 38 releases published
36/36Release recency — latest release 14 days ago
19.8/27Release cadence — a release every ~113.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count38
latest_release_tagv0.18.0
releases_from_tagsno
days_since_latest_release14
mean_days_between_releases113.4
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?

49Weak · 17% of overall
How it's scored
21.1/60Stars — 21 stars
0/25Forks — 1 forks
0/15Watchers — 2 watchers
Inputs used
forks1
stars21
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized 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_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
34.3/80Monthly downloads — 373 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagescascade-ml
dependents—
ecosystemspypi
total_downloads—
monthly_downloads373
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?

57Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
4.1/13.5Contributor breadth — 3 contributors
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.998
How it's scored
42/42Issue resolution — 100% of issues closed
29.9/30PR acceptance — 314/315 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/10 approved changesets -- score normalized to 0
Inputs used
merged_prs314
open_issues0
closed_issues1
prs_merged_7d6
prs_decided_7d6
prs_merged_30d30
prs_decided_30d30
issue_closed_ratio1
closed_unmerged_prs1
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.
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
8/25Owner reach — 12 followers of Oxid15
21.8/25Track record — 21 public repos, account ~9 yr old
Inputs used
followers12
owner_typeUser
is_verified—
owner_loginOxid15
public_repos21
account_age_days3,304
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 14 days ago
20/20Version history — 31 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagescascade-ml
ecosystemspypi
any_deprecatedno
min_days_since_publish14

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests — 1 out of 7 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://oxid15.github.io/cascade/en/latest
10/10Repository description
10/10Topics — 11 topics
10/10Wiki
Inputs used
topicsmachine-learning, ml, mlops, model-selection, model-lifecycle, experiment-tracking, ml-experimentation, small-scale-mlops, data-lineage, local-first, reproducible-research
has_wikiyes
homepagehttps://oxid15.github.io/cascade/en/latest
docs_sitehttps://oxid15.github.io/cascade/en/latest
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

57Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0.2/2.5CI-Tests — 1 out of 7 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/10 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.6
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, 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_packages14
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:cascade-ml@0.18.0 runtime dependency closure — what installing the published package pulls in — 14 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.

37Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
9.6/40Legible commit history — 18 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.18
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — cascade/docs/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filescascade/docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/163 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes17,349
source_files_sampled163
oversized_source_files0

Key facts

21GitHub stars
3contributors
233commits, last 12 months
2days since last push
38releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

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

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 · 2026-09-26 09:35 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
1CI-Tests1 out of 7 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/10 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 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
9Vulnerabilities1 existing vulnerabilities detected
All dependencies 31

Full resolved dependency set from the GitHub dependency graph: 0 direct and 31 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIastunparse—indirect
PyPIclick—indirect
PyPIcoolname—indirect
PyPIdash—indirect
PyPIdash-renderjson0.0.1indirect
PyPIdeepdiff—indirect
PyPIinterrogate—indirect
PyPInbsphinx—indirect
PyPInumpy—indirect
PyPIopencv-python—indirect
PyPIorderly-set5.3.2indirect
PyPIpandas—indirect
PyPIpendulum—indirect
PyPIpillow—indirect
PyPIplotly—indirect
PyPIpydantic—indirect
PyPIpydata-sphinx-theme—indirect
PyPIpytest—indirect
PyPIpytest-cov—indirect
PyPIpyyaml—indirect
PyPIruff—indirect
PyPIscikit-learn—indirect
PyPIsetuptools—indirect
PyPIsphinx—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinx-design—indirect
PyPIsybil—indirect
PyPItorch—indirect
PyPItorchvision—indirect
PyPItqdm—indirect
PyPItyping-extensions—indirect
Dependency advisories 0

Installing pypi:cascade-ml@0.18.0 pulls in 14 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.

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.