Public record
Software health reportschema 0.17.0 · metrics 2.10.0 · 2026-07-21 03:35 UTC

mdolab / sphinx_mdolab_theme

PythonNo license detected★ 3 stars⑂ 4 forkssince Sep 2020View on GitHub ↗

mdolab/sphinx_mdolab_theme holds a health index of 31 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (67/100) and lowest on AI Readiness (11/100). It was last updated 335 days ago. A single contributor accounts for most of its recent work.

31
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.

31
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 37 is calibrated to 31 on the published index scale (record calibration 2026-08-02).

Ownership

MDO LabOrganization
263 followers30 public repossince Apr 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIsphinx_mdolab_theme1.4.454643335 days agosphinxthememdolab

Metrics by category

Vitality

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

29At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 335 days ago
0.7/36Commit cadence1/52 weeks with commits
2.7/18Commit volume1 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year1
human_commit_share
days_since_last_push335
active_weeks_last_year1
How it's scored
27/27Ships releases43 releases published
16.2/36Release recencylatest release 335 days ago
12.6/27Release cadencea release every ~144.3 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count43
latest_release_tagv1.4.4
releases_from_tagsno
days_since_latest_release335
mean_days_between_releases144.3
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?

28At Risk · 17% of overall
How it's scored
4.9/60Stars3 stars
4/25Forks4 forks
4.3/15Watchers7 watchers
Inputs used
forks4
stars3
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonbelow_threshold
How it's scored
22.5/22.5README
0/22.5Licenseno license file detected
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseno
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes
How it's scored
36.5/80Monthly downloads546 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagessphinx_mdolab_theme
dependents
ecosystemspypi
total_downloads
monthly_downloads546
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?

67Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.9/22.5Commit distributiontop contributor authored 87% of commits
12.2/13.5Contributor breadth9 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled9
top_contributor_share0.87
How it's scored
35/42Issue resolution83% of issues closed
30/30PR acceptance13/13 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 9/29 approved changesets -- score normalized to 3
Inputs used
merged_prs13
open_issues1
closed_issues5
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.833
closed_unmerged_prs0
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
17.4/25Owner reach263 followers of mdolab
22.9/25Track record30 public repos, account ~9 yr old
Inputs used
followers263
owner_typeOrganization
is_verified
owner_loginmdolab
public_repos30
account_age_days3,393
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 335 days ago
20/20Version history43 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagessphinx_mdolab_theme
ecosystemspypi
any_deprecatedno
min_days_since_publish335

Engineering Quality

Are baseline engineering and documentation practices in place?

17Critical · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests2 out of 11 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionno

Security

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

42Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0.2/2.5CI-Tests2 out of 11 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 9/29 approved changesets -- score normalized to 3
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
0/2.5Licenselicense file not detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
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-Permissionsno data
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate2.8
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages39
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:sphinx_mdolab_theme@1.4.4 runtime dependency closure — what installing the published package pulls in — 39 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.

11Critical · 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
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
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
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/16 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes28,914
source_files_sampled16
oversized_source_files0

Key facts

3GitHub stars
9contributors
1commits, last 12 months
335days since last push
43releases
1bus factor
1open issues
PyPIpackage ecosystems

More detail

Star and fork history 3 ★ / 0 ⇿
3Stars

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.

12233312021-072023-012024-06

Each point covers 3 days.

OpenSSF Scorecard 2.8 / 10
2.8aggregate

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 · 2026-07-21 03:35 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-Tests2 out of 11 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 9/29 approved changesets -- score normalized to 3
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
0Licenselicense file not detected
0Maintained0 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
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 11

Full resolved dependency set from the GitHub dependency graph: 0 direct and 11 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpyindirect
PyPInumpydocindirect
PyPIpyyamlindirect
PyPIredbaronindirect
PyPIsphinxindirect
PyPIsphinx-copybuttonindirect
PyPIsphinx-promptindirect
PyPIsphinx-rtd-themeindirect
PyPIsphinx-tabsindirect
PyPIsphinxcontrib-autoprogramindirect
PyPIsphinxcontrib-bibtexindirect
Dependency advisories 0

Installing pypi:sphinx_mdolab_theme@1.4.4 pulls in 39 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 v0.17.0 — full methodology · metrics wiki.

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