Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 03:39 UTC

AZX-PBC-OSS / dotenvmodel

Type-safe environment configuration with automatic .env file loading. Pydantic-style fields, intelligent .env cascading, and auto-generated docs.

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

AZX-PBC-OSS/dotenvmodel holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Community & Adoption (51/100). It was last updated 2 days ago. A single contributor accounts for most of its recent work.

87
overall / 100
Excellent

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.

87
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

AZX, PBC. Open SourceOrganization · verified domain
7 followers16 public repossince Mar 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdotenvmodel1.1.04,3361711 days agoconfigconfigurationdotenvenvenvironmentsettings

Metrics by category

Vitality

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

80Excellent · 21% of overall
How it's scored
36/36Push recency — last push 2 days ago
4.2/36Commit cadence — 6/52 weeks with commits
16.4/18Commit volume — 66 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_year66
human_commit_share0.636
days_since_last_push2
active_weeks_last_year6

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 18 releases published
36/36Release recency — latest release 11 days ago
27/27Release cadence — a release every ~4.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count18
latest_release_tagv1.1.0
releases_from_tagsno
days_since_latest_release11
mean_days_between_releases4.5
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?

51Moderate · 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

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes
How it's scored
48.5/80Monthly downloads — 4,336 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdotenvmodel
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,336
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?

60Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1.1/22.5Commit distribution — top contributor authored 95% of commits
2.7/13.5Contributor breadth — 2 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.952
How it's scored
25.7/42Issue resolution — 61% of issues closed
28.8/30PR acceptance — 48/50 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-Review — Found 16/19 approved changesets -- score normalized to 8
Inputs used
merged_prs48
open_issues7
closed_issues11
prs_merged_7d0
prs_decided_7d0
prs_merged_30d7
prs_decided_30d7
issue_closed_ratio0.611
closed_unmerged_prs2
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
30/30Ownership backing — organization-owned
20/20Verified domain
6.5/25Owner reach — 7 followers of AZX-PBC-OSS
10/25Track record — 16 public repos, account ~0 yr old
Inputs used
followers7
owner_typeOrganization
is_verifiedyes
owner_loginAZX-PBC-OSS
public_repos16
account_age_days189

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 11 days ago
20/20Version history — 17 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdotenvmodel
ecosystemspypi
any_deprecatedno
min_days_since_publish11

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 28 out of 28 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://azx-pbc-oss.github.io/dotenvmodel/
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicsdotenv, env, python, python3, typesafety, typing
has_wikiyes
homepagehttps://azx-pbc-oss.github.io/dotenvmodel/
docs_sitehttps://azx-pbc-oss.github.io/dotenvmodel/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

83Excellent · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 28 out of 28 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 16/19 approved changesets -- score normalized to 8
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — 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
5/5Pinned-Dependencies — all dependencies are pinned
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
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.9
Excluded from scoring (no data or not applicable): 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_packages2
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:dotenvmodel@1.1.0 runtime dependency closure — what installing the published package pulls in — 2 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.

76Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 41 of 42 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.976
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — dotenvmodel/py.typed
10/10Reproducible environment — lockfile
3/10Demonstrated agent practice — 1 of the last 66 commits agent-authored or agent-credited
8/8Automated maintenance — 6 of the last 66 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsdotenvmodel/py.typed
agent_commit_share0.015
toolchain_manifests—
dependency_bot_commit_share0.091
How it's scored
27/45Type-checkable code — Python with type-check config (dotenvmodel/py.typed)
52.6/55Manageable file sizes — 3/70 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes99,665
source_files_sampled70
oversized_source_files3
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

4GitHub stars
2contributors
66commits, last 12 months
2days since last push
18releases
1bus factor
7open 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

More detail

OpenSSF Scorecard 7.9 / 10
7.9aggregate

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 03:39 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests28 out of 28 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 16/19 approved changesets -- score normalized to 8
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate 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
10Pinned-Dependenciesall dependencies are pinned
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIpython-dotenv>=1.2.3pyproject.toml
PyPItyping-extensions>=4.16.0pyproject.toml
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

Dependency advisories 0

Installing pypi:dotenvmodel@1.1.0 pulls in 2 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.