Public record
Software health reportschema 0.15.0 · metrics 2.10.0 · 2026-07-19 21:16 UTC

Josverl / micropython-stubs

Stubs of most MicroPython ports, boards and versions to make writing code that much simpler.

PythonMIT★ 311 stars⑂ 30 forkssince Oct 2020View on GitHub ↗

Josverl/micropython-stubs holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Vitality (96/100) and lowest on Security (45/100). It was last updated today. A single contributor accounts for most of its recent work.

78
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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

Jos VerlindePersonal account
72 followers245 public repossince Aug 2011@microsoft

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Metrics by category

Vitality

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

96Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
35.3/36Commit cadence51/52 weeks with commits
18/18Commit volume674 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 12 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year674
human_commit_share
days_since_last_push0
active_weeks_last_year51
How it's scored
27/27Ships releases14 releases published
36/36Release recencylatest release 53 days ago
19.8/27Release cadencea release every ~94.4 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count14
latest_release_tagsetup-stubs_v0.1.28
releases_from_tagsno
days_since_latest_release53
mean_days_between_releases94.4
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?

53Moderate · 17% of overall
How it's scored
40.4/60Stars311 stars
12.2/25Forks30 forks
3.3/15Watchers5 watchers
Inputs used
forks30
stars311
watchers5
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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_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?

46Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.7/22.5Commit distributiontop contributor authored 97% of commits
13.5/13.5Contributor breadth11 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled11
top_contributor_share0.97
How it's scored
34.2/42Issue resolution82% of issues closed
14.9/30PR acceptance357/720 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs357
open_issues29
closed_issues128
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.815
closed_unmerged_prs363
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
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
13.4/25Owner reach72 followers of Josverl
25/25Track record245 public repos, account ~14 yr old
Inputs used
followers72
owner_typeUser
is_verified
owner_loginJosverl
public_repos245
account_age_days5,452
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

88Excellent · 19% of overall
How it's scored
24/24CI workflows13 workflow(s)
24/24Tests present
16/16Linter config.pylintrc
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://micropython-stubs.readthedocs.io
10/10Repository description
10/10Topics13 topics
10/10Wiki
Inputs used
topicsmicropython, vscode, type-checking, static-typing, mypy-stubs, pyright, pylance, pylint, pycharm-ide, type-stubs, awesome-micropython, mypy, pyscript
has_wikiyes
homepagehttps://micropython-stubs.readthedocs.io
docs_sitehttps://micropython-stubs.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

45Weak · 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
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
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
7.5/7.5Maintained30 commit(s) and 12 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
1/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
3.8/7.5Vulnerabilities5 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.5
Excluded from scoring (no data or not applicable): CI-Tests, Packaging, 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.

85Excellent · 4% of overall
How it's scored
45/45Agent instructions.github/copilot-instructions.md
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.github/copilot-instructions.md
agent_instruction_max_bytes10,363
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrapdocs/Makefile, justfile
22/22Automated tests
11/11Lint / format config.pylintrc
11/11Static type checkingpublish/micropython-stdlib-stubs/pyrightconfig.json
10/10Reproducible environmentdevcontainer, Dockerfile
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
2/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_filesdocs/Makefile, justfile
has_devcontaineryes
has_linter_configyes
typecheck_configspublish/micropython-stdlib-stubs/pyrightconfig.json
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
27/45Type-checkable codePython with type-check config (publish/micropython-stdlib-stubs/pyrightconfig.json)
55/55Manageable file sizes8/17,152 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes869,838
source_files_sampled17,152
oversized_source_files8
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
20/20MCP server
40/40Runnable examplesexamples, notebooks, samples
Inputs used
example_dirsexamples, notebooks, samples
has_mcp_signalyes
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

311GitHub stars
11contributors
674commits, last 12 months
0days since last push
14releases
1bus factor
29open issues
PyPIpackage ecosystems

Data collection warnings

  • File tree truncated by GitHub API; file-based signals may be incomplete
  • Could not fetch pypi package 'micropython-stubs' from its registry

More detail

OpenSSF Scorecard 4.5 / 10
4.5aggregate

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 · 2026-07-19 21:15 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
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 12 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
5Vulnerabilities5 existing vulnerabilities detected
All dependencies 13

Full resolved dependency set from the GitHub dependency graph: 0 direct and 13 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIgoogle-cloud-bigqueryindirect
PyPIjinja2indirect
PyPImicropython-stdlib-stubsindirect
PyPImicropython-stubberindirect
PyPImpflashindirect
PyPImyst-parserindirect
PyPIpandasindirect
PyPIpyrightindirect
PyPIpythonindirect
PyPIsphinxindirect
PyPIsphinx-autoapiindirect
PyPIsphinx-rtd-themeindirect
PyPIsphinxcontrib-mermaidindirect
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 v0.15.0 — full methodology · metrics wiki.

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