Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 18:47 UTC

zw008 / VMware-AIops

VMware vCenter/ESXi AI-powered monitoring and operations. Two skills: vmware-monitor (read-only, safe) and vmware-aiops (full operations) | Claude Code Skill

PythonMIT★ 63 stars⑂ 9 forkssince Feb 2026View on GitHub ↗
KindMCP serverLibraryCommand-line toolhow this is determined

zw008/VMware-AIops holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Vitality (87/100) and lowest on Community & Adoption (47/100). It was last updated today. A single contributor accounts for most of its recent work.

69
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.

69
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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

wei zhouPersonal account
18 followers32 public repossince Jan 2015

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIvmware-aiops1.8.8-711 day ago

Metrics by category

Vitality

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

87Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
13.8/36Commit cadence20/52 weeks with commits
18/18Commit volume215 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 9 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year215
human_commit_share0.92
days_since_last_push0
active_weeks_last_year20

Release discipline

100Exceptional
How it's scored
27/27Ships releases70 releases published
36/36Release recencylatest release 1 days ago
27/27Release cadencea release every ~0.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count70
latest_release_tagv1.8.8
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases0.8
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?

47Weak · 17% of overall
How it's scored
29.1/60Stars63 stars
7.5/25Forks9 forks
1.7/15Watchers3 watchers
Inputs used
forks9
stars63
watchers3
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
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

55Moderate · 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
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
42/42Issue resolution100% of issues closed
15/30PR acceptance11/22 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_prs11
open_issues0
closed_issues10
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio1
closed_unmerged_prs11
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
9.2/25Owner reach18 followers of zw008
23.1/25Track record32 public repos, account ~11 yr old
Inputs used
followers18
owner_typeUser
is_verified
owner_loginzw008
public_repos32
account_age_days4,201
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 1 days ago
20/20Version history71 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesvmware-aiops
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

54Moderate · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://skills.sh/zw008/VMware-AIops
10/10Repository description
10/10Topics19 topics
0/10Wiki
Inputs used
topicsagent-skills, aiops, claude-code, codex, devops, esxi, gemini-cli, infrastructure, mcp, pyvmomi, vmware, vsphere, automation, monitoring, vcenter, read-only-monitoring, ai-skill, homelab, vm-lifecycle
has_wikino
homepagehttps://skills.sh/zw008/VMware-AIops
docs_sitehttps://skills.sh/zw008/VMware-AIops
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

67Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
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
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflowno data
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 9 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTno SAST tool detected
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
6.8/7.5Vulnerabilities1 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate5.9
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 advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories1
affected_packages1
assessed_packages54
unassessed_packages0
affected_by_severityhigh 1
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 54 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

54Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history92 of 92 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
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile, lockfile
6/10Demonstrated agent practice3 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance8 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency 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_configno
typecheck_configs
agent_commit_share0.03
toolchain_manifests
dependency_bot_commit_share0.08
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/92 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes45,608
source_files_sampled92
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
20/20MCP server
40/40Runnable examplesexamples
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

63GitHub stars
1contributors
215commits, last 12 months
0days since last push
70releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:vmware-aiops@1.8.8; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 9 ⇿
0Stars
9Forks
47Releases

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.

0246810912026-032026-042026-06
Major 1Minor 7Patch 39
OpenSSF Scorecard 5.9 / 10
5.9aggregate

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 · 2026-07-22 18:47 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
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 9 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 10
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>=1.8.8,<2.0pyproject.toml
PyPIvmware-monitor>=1.8.0,<2.0pyproject.toml
All dependencies 54

Full resolved dependency set from the GitHub dependency graph: 9 direct and 45 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-policy1.8.8direct
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
PyPIcryptography49.0.0indirect
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
PyPIruff0.15.8indirect
PyPIshellingham1.5.4indirect
PyPIsse-starlette3.3.3indirect
PyPIstarlette1.3.1indirect
PyPItomli2.4.1indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.3indirect
PyPItzlocal5.3.1indirect
PyPIuvicorn0.42.0indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 54 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 0 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
click8.3.1indirecthigh18.3.3

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 v0.26.0 — full methodology · metrics wiki.

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