Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 02:21 UTC

vmware-skills / VMware-Monitor

Read-only VMware vCenter/ESXi monitoring — code-level enforced safety, zero destructive operations

PythonMIT★ 12 stars⑂ 4 forkssince Feb 2026View on GitHub ↗
KindCommand-line toolMCP serverhow this is determined
#ai-skill#aiops#claude-code#codex#esxi#gemini-cli#homelab#infrastructure#mcp#monitoring#pyvmomi#read-only#vcenter#vmware#vsphere#agent-skills

vmware-skills/VMware-Monitor holds a health index of 73 out of 100, placing it in the Good band. It scores highest on Vitality (89/100) and lowest on Community & Adoption (43/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

73
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.

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

Ownership

vmware-skillsOrganization
5 followers16 public repossince Aug 2026

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIvmware-monitor1.11.32,751861 day ago

Metrics by category

Vitality

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

89Excellent · 21% of overall

Development activity

81Excellent
How it's scored
36/36Push recency — last push 1 days ago
17.3/36Commit cadence — 25/52 weeks with commits
18/18Commit volume — 218 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year218
human_commit_share0.98
days_since_last_push1
active_weeks_last_year25

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 84 releases published
36/36Release recency — latest release 1 days ago
27/27Release cadence — a release every ~1.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count84
latest_release_tagv1.11.3
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases1.4
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?

43Weak · 17% of overall

Popularity & adoption

21At Risk
How it's scored
16.9/60Stars — 12 stars
4/25Forks — 4 forks
0/15Watchers — 0 watchers
Inputs used
forks4
stars12
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

57Moderate
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

57Moderate
How it's scored
45.9/80Monthly downloads — 2,751 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesvmware-monitor
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,751
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?

54Moderate · 23% of overall

Maintainer resilience (bus factor)

22At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.1/22.5Commit distribution — top contributor authored 99% of commits
2.7/13.5Contributor breadth — 2 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.994

Issue & PR responsiveness

66Good
How it's scored
42/42Issue resolution — 100% of issues closed
15.7/30PR acceptance — 12/23 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs12
open_issues0
closed_issues3
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs11
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.

Ownership & stewardship

45Weak
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
5.6/25Owner reach — 5 followers of vmware-skills
9.2/25Track record — 16 public repos, account ~0 yr old
Inputs used
followers5
owner_typeOrganization
is_verifiedno
owner_loginvmware-skills
public_repos16
account_age_days43

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 1 days ago
20/20Version history — 86 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesvmware-monitor
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

64Moderate · 19% of overall

Engineering practices

50Moderate
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_cino
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

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 16 topics
10/10Wiki
Inputs used
topicsai-skill, aiops, claude-code, codex, esxi, gemini-cli, homelab, infrastructure, mcp, monitoring, pyvmomi, read-only, vcenter, vmware, vsphere, agent-skills
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

68Good · 16% of overall

Security posture

60Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
0/10Dangerous-Workflow — no data
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 1 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 — no SAST tool detected
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — no data
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate6
Excluded from scoring (no data or not applicable): Branch-Protection, CI-Tests, Dangerous-Workflow, Packaging, Signed-Releases, Token-Permissions. 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_packages42
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:vmware-monitor@1.11.3 runtime dependency closure — what installing the published package pulls in — 42 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.

60Moderate · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 98 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

61Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 2 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.06
toolchain_manifests—
dependency_bot_commit_share0.02

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/108 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes52,319
source_files_sampled108
oversized_source_files0

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

12GitHub stars
2contributors
218commits, last 12 months
1days since last push
84releases
1bus factor
0open issues
npm, PyPIpackage ecosystems

Data collection warnings

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

More detail

Star and fork history 0 ★ / 4 ⇿
0Stars
4Forks
67Releases

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.

1223344412026-032026-052026-07
Major 0Minor 8Patch 59
OpenSSF Scorecard 6.0 / 10
6.0aggregate

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 02:21 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
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
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 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
0SASTno SAST tool detected
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
9Vulnerabilities1 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPIpyvmomi>=8.0.3.0,<10.0pyproject.toml
PyPIpyaml>=24.0,<27.0pyproject.toml
PyPItyper>=0.12,<1.0pyproject.toml
PyPIrich>=13.0,<16.0pyproject.toml
PyPIapscheduler>=3.10,<4.0pyproject.toml
PyPIhttpx>=0.27,<1.0pyproject.toml
PyPIpython-dotenv>=1.0,<2.0pyproject.toml
PyPImcp>=1.10,<2.0pyproject.toml
PyPIvmware-policy>=1.13.1,<2.0pyproject.toml
All dependencies 55

Full resolved dependency set from the GitHub dependency graph: 9 direct and 46 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIapscheduler3.11.2direct
PyPIhttpx0.28.1direct
PyPImcp1.28.1direct
PyPIpyaml26.2.1direct
PyPIpython-dotenv1.2.2direct
PyPIpyvmomi9.0.0.0direct
PyPIrich14.3.3direct
PyPItyper0.24.1direct
PyPIvmware-policy1.13.1direct
PyPIannotated-doc0.0.4indirect
PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIattrs26.1.0indirect
PyPIcertifi2026.2.25indirect
PyPIcffi2.0.0indirect
PyPIclick8.3.1indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.5indirect
PyPIcryptography50.0.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx-sse0.4.3indirect
PyPIidna3.15indirect
PyPIiniconfig2.3.0indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImarkdown-it-py4.0.0indirect
PyPImdurl0.1.2indirect
PyPIpackaging26.0indirect
PyPIpluggy1.6.0indirect
PyPIpycparser3.0indirect
PyPIpydantic2.12.5indirect
PyPIpydantic-core2.41.5indirect
PyPIpydantic-settings2.14.2indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.13.0indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32311indirect
PyPIpyyaml6.0.3indirect
PyPIreferencing0.37.0indirect
PyPIrpds-py0.30.0indirect
PyPIruff0.15.9indirect
PyPIshellingham1.5.4indirect
PyPIsse-starlette3.3.4indirect
PyPIstarlette1.3.1indirect
PyPItomli2.4.1indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2026.1indirect
PyPItzlocal5.3.1indirect
PyPIuvicorn0.42.0indirect
PyPIvmware-monitor1.11.3indirect
Dependency advisories 0

Installing pypi:vmware-monitor@1.11.3 pulls in 42 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.

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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.