Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-23 09:24 UTC

OpenHCSDev / ZMQRuntime

PythonMIT★ 0 stars⑂ 0 forkssince Jan 2026View on GitHub ↗

OpenHCSDev/ZMQRuntime holds a health index of 59 out of 100, placing it in the Moderate band. It scores highest on Vitality (80/100) and lowest on Community & Adoption (35/100). It was last updated today. A single contributor accounts for most of its recent work.

59
overall / 100
Moderate

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.

59
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 56 is calibrated to 59 on the published index scale (record calibration 2026-08-02).

Ownership

OpenHCSDevOrganization
2 followers11 public repossince Jan 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIzmqruntime0.2.1117,040340 days agodistributedexecutionmessagingrpczeromqzmq

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 recencylast push 0 days ago
9.7/36Commit cadence14/52 weeks with commits
17.3/18Commit volume83 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year83
human_commit_share1
days_since_last_push0
active_weeks_last_year14
How it's scored
27/27Ships releases35 releases published
36/36Release recencylatest release 0 days ago
27/27Release cadencea release every ~1.2 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count35
latest_release_tagv0.2.11
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1.2

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

35Weak · 17% of overall
How it's scored
0/60Stars0 stars
0/25Forks0 forks
0/15Watchers0 watchers
Inputs used
forks0
stars0
watchers0
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
56.4/80Monthly downloads17,040 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packageszmqruntime
dependents
ecosystemspypi
total_downloads
monthly_downloads17,040
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?

48Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0/22.5Commit distributiontop contributor authored 100% of commits
1.4/13.5Contributor breadth1 contributors
0/10OpenSSF Scorecard: Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
0/42Issue resolutionno issues or no data
20/30PR acceptance2/3 decided PRs merged
13/13Newcomer PR acceptance2/2 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 1/28 approved changesets -- score normalized to 0
Inputs used
merged_prs2
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio
closed_unmerged_prs1
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d2
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
3.4/25Owner reach2 followers of OpenHCSDev
9.1/25Track record11 public repos, account ~0 yr old
Inputs used
followers2
owner_typeOrganization
is_verifiedno
owner_loginOpenHCSDev
public_repos11
account_age_days222

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history34 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packageszmqruntime
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff], [tool.black])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 2 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://zmqruntime.readthedocs.io
0/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_sitehttps://zmqruntime.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

47Weak · 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-Tests0 out of 2 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 1/28 approved changesets -- score normalized to 0
0/2.5Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
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 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
2/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate4.7

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 instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
16.2/40Legible commit history27 of 89 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.303
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff], [tool.black])
0/11Static type checking
0/10Reproducible environment
2.2/10Demonstrated agent practice1 of the last 89 commits agent-authored or agent-credited
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
4/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.011
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/53 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes45,417
source_files_sampled53
oversized_source_files0

Key facts

0GitHub stars
1contributors
83commits, last 12 months
0days since last push
35releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:zmqruntime@0.2.11; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 4.7 / 10
4.7aggregate

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 · 2026-08-23 09:24 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 2 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/28 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
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
10Packagingpackaging workflow detected
4Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 4
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIannotated-types>=0.7.0pyproject.toml
PyPImetaclass-registry>=0.1.6pyproject.toml
PyPInumpy>=1.24pyproject.toml
PyPIpyzmq>=22.0pyproject.toml
PyPIpsutil>=5.9pyproject.toml
PyPIpython-introspect>=0.1.6pyproject.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

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 statisticsPyPI.