Public record
Software health reportschema 0.27.0 · metrics 2.10.0 · 2026-07-26 09:40 UTC

linkml / linkml-model

Link Modeling Language (LinkML) model

PythonCC0-1.0★ 79 stars⑂ 29 forkssince Mar 2021View on GitHub ↗
KindLibraryhow this is determined
#linkml#semantic-web#json#json-schema#graph-ql#metamodel#yaml#data-integration#metadata#uml#schema-language#data-modeling#shacl#shex#linked-data

linkml/linkml-model holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (85/100) and lowest on Community & Adoption (57/100). It was last updated 10 days ago. 2 contributors account for most of its recent work.

86
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.

86
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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

Linked data Modeling LanguageOrganization
218 followers67 public repossince Feb 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIlinkml-model1.8.01,22933752 days agolinked-datalinkmlmetamodel

Metrics by category

Vitality

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

72Good · 21% of overall

Development activity

59Moderate
How it's scored
28.8/36Push recency — last push 10 days ago
8.3/36Commit cadence — 12/52 weeks with commits
13.3/18Commit volume — 29 commits in the last year
9/10OpenSSF Scorecard: Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
Inputs used
commits_last_year29
human_commit_share0.97
days_since_last_push10
active_weeks_last_year12

Release discipline

92Excellent
How it's scored
27/27Ships releases — 42 releases published
36/36Release recency — latest release 73 days ago
19.8/27Release cadence — a release every ~76.1 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count42
latest_release_tagv1.11.0
releases_from_tagsno
days_since_latest_release73
mean_days_between_releases76.1
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?

57Moderate · 17% of overall

Popularity & adoption

49Weak
How it's scored
30.7/60Stars — 79 stars
12.1/25Forks — 29 forks
5.8/15Watchers — 12 watchers
Inputs used
forks29
stars79
watchers12
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (CC0-1.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

52Moderate
How it's scored
41.2/80Monthly downloads — 1,229 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageslinkml-model
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,229
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?

77Good · 23% of overall

Maintainer resilience (bus factor)

61Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.9/22.5Commit distribution — top contributor authored 47% of commits
13.5/13.5Contributor breadth — 22 contributors
10/10OpenSSF Scorecard: Contributors — project has 65 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled22
top_contributor_share0.473

Issue & PR responsiveness

90Excellent
How it's scored
40.1/42Issue resolution — 96% of issues closed
26/30PR acceptance — 177/204 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
12/15OpenSSF Scorecard: Code-Review — Found 19/23 approved changesets -- score normalized to 8
Inputs used
merged_prs177
open_issues1
closed_issues21
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.955
closed_unmerged_prs27
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.

Ownership & stewardship

88Excellent
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
16.8/25Owner reach — 218 followers of linkml
23.9/25Track record — 67 public repos, account ~5 yr old
Inputs used
followers218
owner_typeOrganization
is_verified—
owner_loginlinkml
public_repos67
account_age_days1,982
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

69Good
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 752 days ago
20/20Version history — 33 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslinkml-model
ecosystemspypi
any_deprecatedno
min_days_since_publish752

Engineering Quality

Are baseline engineering and documentation practices in place?

85Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 24 out of 25 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

75Good
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://linkml.github.io/linkml-model/docs/
10/10Repository description
10/10Topics — 15 topics
10/10Wiki
Inputs used
topicslinkml, semantic-web, json, json-schema, graph-ql, metamodel, yaml, data-integration, metadata, uml, schema-language, data-modeling, shacl, shex, linked-data
has_wikiyes
homepagehttps://linkml.github.io/linkml-model/docs/
docs_sitehttps://linkml.github.io/linkml-model/docs/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

70Good · 16% of overall

Security posture

62Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.2/2.5CI-Tests — 24 out of 25 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 19/23 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 65 contributing companies or organizations
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
6.8/7.5Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.2
Excluded from scoring (no data or not applicable): Branch-Protection, 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_packages31
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:linkml-model@1.8.0 runtime dependency closure — what installing the published package pulls in — 31 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.

58Moderate · 4% of overall

Agent context & guidance

24At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
24.2/40Legible commit history — 44 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.454
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

71Good
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 3 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_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.03

Code legibility for models

52Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
52.1/55Manageable file sizes — 1/19 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes311,261
source_files_sampled19
oversized_source_files1

Machine-readable interfaces

100Exceptional
How it's scored
40/40API schema (OpenAPI/GraphQL/proto) — linkml_model/graphql/meta.graphql, linkml_model/protobuf/meta.proto
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
has_mcp_signalno
api_schema_fileslinkml_model/graphql/meta.graphql, linkml_model/protobuf/meta.proto
interfaces_expected_of—
Excluded from scoring (no data or not applicable): MCP server. Remaining weights renormalized.

Key facts

79GitHub stars
22contributors
29commits, last 12 months
10days since last push
42releases
2bus factor
1open issues
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 ★ / 29 ⇿
0Stars
29Forks
34Releases

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.

0510152025302822021-102024-022026-06
Major 0Minor 9Patch 9

Each point covers 5 days.

OpenSSF Scorecard 6.2 / 10
6.2aggregate

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 · 2026-07-26 09:40 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
9CI-Tests24 out of 25 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 19/23 approved changesets -- score normalized to 8
10Contributorsproject has 65 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
9Maintained11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPIlinkml-runtime==1.11.1,<2pyproject.toml
PyPIlinkml==1.11.1pyproject.toml
All dependencies 115

Full resolved dependency set from the GitHub dependency graph: 2 direct and 113 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIlinkml1.11.1direct
PyPIlinkml-runtime1.11.1direct
PyPIalabaster1.0.0indirect
PyPIannotated-types0.7.0indirect
PyPIantlr4-python3-runtime4.9.3indirect
PyPIarrow1.4.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbackports-zstd1.6.0indirect
PyPIbackrefs7.0indirect
PyPIbeautifulsoup44.15.0indirect
PyPIcertifi2026.6.17indirect
PyPIcfgraph0.2.1indirect
PyPIchardet7.4.3indirect
PyPIcharset-normalizer3.4.7indirect
PyPIclick8.4.1indirect
PyPIcodespell2.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcuries0.13.13indirect
PyPIdeprecated1.3.1indirect
PyPIdocutils0.21.2indirect
PyPIdocutils0.22.4indirect
PyPIeditorconfig0.17.1indirect
PyPIet-xmlfile2.0.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIfqdn1.5.1indirect
PyPIghp-import2.1.0indirect
PyPIgraphviz0.21indirect
PyPIgreenlet3.5.2indirect
PyPIhbreader0.9.1indirect
PyPIidna3.18indirect
PyPIimagesize2.0.0indirect
PyPIiniconfig2.3.0indirect
PyPIisodate0.7.2indirect
PyPIisoduration20.11.0indirect
PyPIjinja23.1.6indirect
PyPIjsbeautifier2.0.1indirect
PyPIjson-flattener0.1.9indirect
PyPIjsonasobj1.3.1indirect
PyPIjsonasobj21.0.4indirect
PyPIjsonpointer3.1.1indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPImarkdown3.10.2indirect
PyPImarkupsafe3.0.3indirect
PyPImergedeep1.3.4indirect
PyPImike2.2.0indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-material9.7.6indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImkdocs-mermaid2-plugin1.2.3indirect
PyPIopenpyxl3.1.5indirect
PyPIpackaging26.2indirect
PyPIpaginate0.5.7indirect
PyPIparse1.22.1indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.10.0indirect
PyPIpluggy1.6.0indirect
PyPIprefixcommons0.1.12indirect
PyPIprefixmaps0.2.6indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpyjsg0.12.4indirect
PyPIpymdown-extensions10.21.3indirect
PyPIpyparsing3.3.2indirect
PyPIpyshex0.9.0indirect
PyPIpyshexc0.10.3.post1indirect
PyPIpystow0.8.19indirect
PyPIpytest9.1.1indirect
PyPIpytest-logging2015.11.4indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIrdflib7.6.0indirect
PyPIrdflib-jsonld0.6.1indirect
PyPIrdflib-shim1.0.3indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc39871.3.8indirect
PyPIroman-numerals4.1.0indirect
PyPIrpds-py0.30.0indirect
PyPIrpds-py2026.5.1indirect
PyPIsetuptools82.0.1indirect
PyPIshexjsg0.9.0indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsoupsieve2.8.4indirect
PyPIsparqlslurper0.5.1indirect
PyPIsparqlwrapper2.0.0indirect
PyPIsphinx8.1.3indirect
PyPIsphinx9.0.4indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-click6.2.0indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlalchemy2.0.51indirect
PyPItomli2.4.1indirect
PyPItqdm4.68.3indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2026.2indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.7.0indirect
PyPIverspec0.1.0indirect
PyPIwatchdog6.0.0indirect
PyPIwebcolors25.10.0indirect
PyPIwrapt2.2.2indirect
PyPIyamllint1.38.0indirect
Dependency advisories 0

Installing pypi:linkml-model@1.8.0 pulls in 31 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.

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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 v0.27.0 — full methodology · metrics wiki.

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