Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-16 07:06 UTC

MinishLab / model2vec

Fast State-of-the-Art Static Embeddings

Python · Jupyter NotebookMIT★ 2,206 stars⑂ 126 forkssince Jul 2024View on GitHub ↗
KindLibraryhow this is determined
#embeddings#machine-learning#model2vec#nlp#python#sentence-transformers#ai#word-embeddings

MinishLab/model2vec holds a health index of 90 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (92/100) and lowest on Security (61/100). It was last updated today. A single contributor accounts for most of its recent work.

90
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.

90
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 76 is calibrated to 90 on the published index scale (record calibration 2026-08-02).

Ownership

MinishOrganization
393 followers12 public repossince Aug 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPImodel2vec0.9.01,200,6052734 days ago

Metrics by category

Vitality

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

84Excellent · 21% of overall

Development activity

79Good
How it's scored
36/36Push recency — last push 0 days ago
16.6/36Commit cadence — 24/52 weeks with commits
16.5/18Commit volume — 67 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year67
human_commit_share1
days_since_last_push0
active_weeks_last_year24

Release discipline

92Excellent
How it's scored
27/27Ships releases — 27 releases published
36/36Release recency — latest release 34 days ago
19.8/27Release cadence — a release every ~61.4 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count27
latest_release_tagv0.9.0
releases_from_tagsno
days_since_latest_release34
mean_days_between_releases61.4
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?

74Good · 17% of overall

Popularity & adoption

78Good
How it's scored
54.2/60Stars — 2,206 stars
17.5/25Forks — 126 forks
6.4/15Watchers — 15 watchers
Inputs used
forks126
stars2,206
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicescodecov.io, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

100Exceptional
How it's scored
80/80Monthly downloads — 1,200,605 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmodel2vec
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1,200,605
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?

69Good · 23% of overall

Maintainer resilience (bus factor)

41Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
8.3/22.5Commit distribution — top contributor authored 63% of commits
13.5/13.5Contributor breadth — 12 contributors
10/10OpenSSF Scorecard: Contributors — project has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled12
top_contributor_share0.632

Issue & PR responsiveness

87Excellent
How it's scored
41.5/42Issue resolution — 99% of issues closed
28.8/30PR acceptance — 266/277 decided PRs merged
10.8/13Newcomer PR acceptance — 5/6 first-time contributors' PRs merged in 30d
6/15OpenSSF Scorecard: Code-Review — Found 13/30 approved changesets -- score normalized to 4
Inputs used
merged_prs266
open_issues1
closed_issues76
prs_merged_7d9
prs_decided_7d10
prs_merged_30d22
prs_decided_30d23
issue_closed_ratio0.987
closed_unmerged_prs11
first_time_authors_30d2
first_time_prs_merged_30d5
first_time_prs_decided_30d6

Ownership & stewardship

61Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
18.7/25Owner reach — 393 followers of MinishLab
12.3/25Track record — 12 public repos, account ~2 yr old
Inputs used
followers393
owner_typeOrganization
is_verifiedno
owner_loginMinishLab
public_repos12
account_age_days767

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 34 days ago
20/20Version history — 27 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmodel2vec
ecosystemspypi
any_deprecatedno
min_days_since_publish34

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 2 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://minish.ai/packages/model2vec/introduction
10/10Repository description
10/10Topics — 8 topics
0/10Wiki
Inputs used
topicsembeddings, machine-learning, model2vec, nlp, python, sentence-transformers, ai, word-embeddings
has_wikino
homepagehttps://minish.ai/packages/model2vec/introduction
docs_sitehttps://minish.ai/packages/model2vec/introduction
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

61Moderate · 16% of overall

Security posture

51Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
3/7.5Code-Review — Found 13/30 approved changesets -- score normalized to 4
2.5/2.5Contributors — project has 4 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
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
0/7.5Vulnerabilities — 17 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.1
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_packages22
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:model2vec@0.9.0 runtime dependency closure — what installing the published package pulls in — 22 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.

72Good · 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 — 100 of 100 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)

82Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — model2vec/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configsmodel2vec/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (model2vec/py.typed)
55/55Manageable file sizes — 0/52 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes25,676
source_files_sampled52
oversized_source_files0

Machine-readable interfaces

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

Key facts

2,206GitHub stars
12contributors
67commits, last 12 months
0days since last push
27releases
1bus 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 ★ / 126 ⇿
0Stars
126Forks
24Releases

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.

0255075100125150126172024-092025-092026-09
Major 0Minor 8Patch 16

Each point covers 2 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-09-16 07:06 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
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 13/30 approved changesets -- score normalized to 4
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update 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
10Pinned-Dependenciesall dependencies are pinned
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
0Vulnerabilities17 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPIjinja2—pyproject.toml
PyPIjoblib—pyproject.toml
PyPInumpy—pyproject.toml
PyPIsafetensors—pyproject.toml
PyPItokenizers>=0.20pyproject.toml
PyPItqdm—pyproject.toml
PyPIhuggingface-hub>=1.0.0pyproject.toml
All dependencies 141

Full resolved dependency set from the GitHub dependency graph: 8 direct and 133 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhuggingface-hub1.8.0direct
PyPIjinja23.1.6direct
PyPIjoblib1.5.3direct
PyPInumpy2.2.6direct
PyPInumpy2.4.3direct
PyPIsafetensors0.7.0direct
PyPItokenizers0.22.2direct
PyPItqdm4.67.3direct
PyPIaiohappyeyeballs2.7.1indirect
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PyPIaiosignal1.4.0indirect
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PyPIannotated-types0.7.0indirect
PyPIanyio4.13.0indirect
PyPIasttokens3.0.1indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs26.1.0indirect
PyPIcertifi2026.2.25indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.9indirect
PyPIclick8.3.1indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.5indirect
PyPIcuda-bindings12.9.4indirect
PyPIcuda-pathfinder1.5.0indirect
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PyPIdecorator5.2.1indirect
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PyPIflatbuffers25.12.19indirect
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PyPInvidia-nvtx-cu1212.8.90indirect
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PyPIpackaging26.0indirect
PyPIpandas2.3.3indirect
PyPIpandas3.0.5indirect
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PyPIpexpect4.9.0indirect
PyPIplatformdirs4.9.4indirect
PyPIpluggy1.6.0indirect
PyPIpolars1.43.2indirect
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PyPIpydantic2.12.5indirect
PyPIpydantic-core2.41.5indirect
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PyPIpytest9.0.2indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.2.1indirect
PyPIpytrec-eval-terrier0.5.10indirect
PyPIpytz2026.3.post1indirect
PyPIpyyaml6.0.3indirect
PyPIregex2026.2.28indirect
PyPIrequests2.34.2indirect
PyPIrich14.3.3indirect
PyPIruff0.15.8indirect
PyPIscikit-learn1.7.2indirect
PyPIscikit-learn1.8.0indirect
PyPIscipy1.15.3indirect
PyPIscipy1.17.1indirect
PyPIsentence-transformers5.6.1indirect
PyPIsetuptools82.0.1indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIskeletoken0.6.0indirect
PyPIskops0.13.0indirect
PyPIstack-data0.6.3indirect
PyPIsympy1.14.0indirect
PyPIthreadpoolctl3.6.0indirect
PyPItomli2.4.1indirect
PyPItorch2.10.0indirect
PyPItraitlets5.14.3indirect
PyPItransformers5.3.0indirect
PyPItriton3.6.0indirect
PyPItyper0.24.1indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2026.3indirect
PyPIurllib32.7.0indirect
PyPIvirtualenv21.2.0indirect
PyPIwcwidth0.6.0indirect
PyPIxxhash3.8.1indirect
PyPIyarl1.24.5indirect
Dependency advisories 0

Installing pypi:model2vec@0.9.0 pulls in 22 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

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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.