Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-30 19:01 UTC

jupyterlab-contrib / spellchecker

Spellchecker for JupyterLab notebook markdown cells and file editor.

TypeScript · PythonBSD-3-Clause★ 212 stars⑂ 22 forkssince Apr 2018View on GitHub ↗

jupyterlab-contrib/spellchecker holds a health index of 71 out of 100, placing it in the Good band. It scores highest on Engineering Quality (68/100) and lowest on AI Readiness (56/100). It was last updated 19 days ago. A single contributor accounts for most of its recent work.

71
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.

71
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 63 is calibrated to 71 on the published index scale (record calibration 2026-08-02).

Ownership

93 followers49 public repossince Dec 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIjupyterlab-spellchecker0.9.014,8651455 days ago

Metrics by category

Vitality

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

62Moderate · 21% of overall
How it's scored
28.8/36Push recencylast push 19 days ago
2.1/36Commit cadence3/52 weeks with commits
8.6/18Commit volume8 commits in the last year
9/10OpenSSF Scorecard: Maintained8 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 9
Inputs used
commits_last_year8
human_commit_share0.81
days_since_last_push19
active_weeks_last_year3
How it's scored
27/27Ships releases14 releases published
36/36Release recencylatest release 55 days ago
12.6/27Release cadencea release every ~200.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count14
latest_release_tagv0.9.0
releases_from_tagsno
days_since_latest_release55
mean_days_between_releases200.1
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?

62Moderate · 17% of overall
How it's scored
37.7/60Stars212 stars
11/25Forks22 forks
5/15Watchers9 watchers
Inputs used
forks22
stars212
watchers9
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
55.6/80Monthly downloads14,865 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesjupyterlab-spellchecker
dependents
ecosystemspypi
total_downloads
monthly_downloads14,865
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?

64Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
6.2/22.5Commit distributiontop contributor authored 73% of commits
8.1/13.5Contributor breadth6 contributors
10/10OpenSSF Scorecard: Contributorsproject has 12 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled6
top_contributor_share0.726
How it's scored
29.1/42Issue resolution69% of issues closed
25.9/30PR acceptance83/96 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-ReviewFound 4/12 approved changesets -- score normalized to 3
Inputs used
merged_prs83
open_issues19
closed_issues43
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.694
closed_unmerged_prs13
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.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
14.2/25Owner reach93 followers of jupyterlab-contrib
23.7/25Track record49 public repos, account ~5 yr old
Inputs used
followers93
owner_typeOrganization
is_verifiedno
owner_loginjupyterlab-contrib
public_repos49
account_age_days2,069

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 55 days ago
20/20Version history14 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesjupyterlab-spellchecker
ecosystemspypi
any_deprecatedno
min_days_since_publish55

Engineering Quality

Are baseline engineering and documentation practices in place?

68Good · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config.eslintrc.js
0/9.6Pre-commit hooks
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests8 out of 15 merged PRs checked by a CI test -- score normalized to 5
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicsjupyterlab-extension, jupyterlab
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

58Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
1.2/2.5CI-Tests8 out of 15 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-ReviewFound 4/12 approved changesets -- score normalized to 3
2.5/2.5Contributorsproject has 12 contributing companies or organizations
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
6.8/7.5Maintained8 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 9
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities46 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.7
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages90
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:jupyterlab-spellchecker@0.9.0 runtime dependency closure — what installing the published package pulls in — 90 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.

56Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.3/40Legible commit history40 of 81 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.494
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config.eslintrc.js
11/11Static type checkingtsconfig.json
10/10Reproducible environmentlockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance19 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
lockfilesyarn.lock
has_dockerfileno
typed_languageyes
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configstsconfig.json
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.19
How it's scored
45/45Type-checkable codeTypeScript (statically typed)
55/55Manageable file sizes0/11 source files over 60KB
Inputs used
primary_languageTypeScript
largest_source_bytes25,832
source_files_sampled11
oversized_source_files0

Key facts

212GitHub stars
6contributors
8commits, last 12 months
19days since last push
14releases
1bus factor
19open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch npm package '@jupyterlab-contrib/spellchecker' from its registry

More detail

Star and fork history 0 ★ / 22 ⇿
0Stars
22Forks
13Releases

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.

048121620242222018-052022-052026-06
Major 0Minor 4Patch 9

Each point covers 8 days.

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 · 2026-08-30 19:00 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
5CI-Tests8 out of 15 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 4/12 approved changesets -- score normalized to 3
10Contributorsproject has 12 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
9Maintained8 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 9
n/aPackagingpackaging workflow not 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
0Vulnerabilities46 existing vulnerabilities detected
Direct dependencies 14
RegistryPackageVersion constraintManifest
npm@jupyterlab/application^4.0.2package.json
npm@jupyterlab/apputils^4.1.2package.json
npm@jupyterlab/cells^4.0.2package.json
npm@jupyterlab/codemirror^4.0.2package.json
npm@jupyterlab/fileeditor^4.0.2package.json
npm@jupyterlab/notebook^4.0.2package.json
npm@jupyterlab/settingregistry^4.0.2package.json
npm@jupyterlab/statusbar^4.0.2package.json
npm@jupyterlab/translation^4.0.2package.json
npm@jupyterlab/ui-components^4.0.2package.json
npm@lumino/widgets^2.0.1package.json
npmtypo-js^1.1.0package.json
PyPIjupyter_server>=2.0.1,<3pyproject.toml
PyPIjupyterlab>=4,<5pyproject.toml
All dependencies 584

Full resolved dependency set from the GitHub dependency graph: 14 direct and 570 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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Dependency advisories 0

Installing pypi:jupyterlab-spellchecker@0.9.0 pulls in 90 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 v0.34.0 — full methodology · metrics wiki.

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