Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 21:01 UTC

labsyspharm / cylinter

An Interactive Image Segmentation Filter for Multiplex Microscopy

PythonMIT★ 36 stars⑂ 15 forkssince Jul 2020View on GitHub ↗
KindCommand-line toolLibraryDesktop applicationhow this is determined

labsyspharm/cylinter holds a health index of 47 out of 100, placing it in the Weak band. It scores highest on Sustainability & Governance (62/100) and lowest on AI Readiness (34/100). It was last updated 51 days ago. A single contributor accounts for most of its recent work.

47
overall / 100
Weak

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.

47
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 48 is calibrated to 47 on the published index scale (record calibration 2026-08-02).

Ownership

103 followers188 public repossince Jan 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPICyLinter0.0.45144451264 days agoscriptssinglecelldatascience

Metrics by category

Vitality

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

59Moderate · 21% of overall
How it's scored
18/36Push recency — last push 51 days ago
3.5/36Commit cadence — 5/52 weeks with commits
10.8/18Commit volume — 15 commits in the last year
5/10OpenSSF Scorecard: Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year15
human_commit_share1
days_since_last_push51
active_weeks_last_year5
How it's scored
27/27Ships releases — 13 releases published
36/36Release recency — latest release 51 days ago
19.8/27Release cadence — a release every ~99.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count13
latest_release_tagv0.0.57
releases_from_tagsno
days_since_latest_release51
mean_days_between_releases99.6
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?

40Weak · 17% of overall
How it's scored
25/60Stars — 36 stars
9.6/25Forks — 15 forks
0/15Watchers — 1 watchers
Inputs used
forks15
stars36
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno
How it's scored
28.8/80Monthly downloads — 144 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesCyLinter
dependents—
ecosystemspypi
total_downloads—
monthly_downloads144
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?

62Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9.1/22.5Commit distribution — top contributor authored 60% of commits
6.8/13.5Contributor breadth — 5 contributors
10/10OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.595
How it's scored
40.3/42Issue resolution — 96% of issues closed
28.4/30PR acceptance — 199/210 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 1/30 approved changesets -- score normalized to 0
Inputs used
merged_prs199
open_issues1
closed_issues24
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.96
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.
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
14.5/25Owner reach — 103 followers of labsyspharm
25/25Track record — 188 public repos, account ~7 yr old
Inputs used
followers103
owner_typeOrganization
is_verifiedno
owner_loginlabsyspharm
public_repos188
account_age_days2,819
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
4/35Publish recency — latest publish 1,264 days ago
20/20Version history — 45 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesCyLinter
ecosystemspypi
any_deprecatedno
min_days_since_publish1,264

Engineering Quality

Are baseline engineering and documentation practices in place?

37Weak · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 29 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://labsyspharm.github.io/cylinter/
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics—
has_wikiyes
homepagehttps://labsyspharm.github.io/cylinter/
docs_sitehttps://labsyspharm.github.io/cylinter/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

41Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — 0 out of 29 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 1/30 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 7 contributing companies or organizations
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
3.8/7.5Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
0/5Packaging — no data
0/5Pinned-Dependencies — no data
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 — no data
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate3.4
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized.
How it's scored
17.6/35Direct dependencies free of known advisories — 1 affected: pypdf2 3.0.1 (moderate 6.2)
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
34.6/40No advisories left outstanding — 1 advisory-carrying package(s) unaddressed past 90 days; oldest published 1,206 days ago
Inputs used
sourceosv
advisories11
affected_packages3
assessed_packages141
unassessed_packages0
affected_by_severityhigh 2, moderate 1
direct_affected_packages1
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 141 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.

34At Risk · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
34.1/40Legible commit history — 64 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.64
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsno
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable code — Python without a type-check config
50.2/55Manageable file sizes — 2/23 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes91,737
source_files_sampled23
oversized_source_files2
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

36GitHub stars
5contributors
15commits, last 12 months
51days since last push
13releases
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 ★ / 15 ⇿
0Stars
15Forks
12Releases

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.

03581013151522020-072023-072026-08
Major 0Minor 0Patch 11

Each point covers 6 days.

OpenSSF Scorecard 3.4 / 10
3.4aggregate

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 · 2026-10-18 21:01 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 29 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/30 approved changesets -- score normalized to 0
10Contributorsproject has 7 contributing companies or organizations
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 25
RegistryPackageVersion constraintManifest
PyPIcellcutter=0.2.13pyproject.toml
PyPIhdbscan*pyproject.toml
PyPIjoblib*pyproject.toml
PyPImagicgui*pyproject.toml
PyPImatplotlib*pyproject.toml
PyPInapari>=0.9.0pyproject.toml
PyPInumpy*pyproject.toml
PyPInatsort*pyproject.toml
PyPInumba*pyproject.toml
PyPIpandas*pyproject.toml
PyPIpyarrow*pyproject.toml
PyPIpyqt6*pyproject.toml
PyPIpyqt6-qt6*pyproject.toml
PyPIpyyaml*pyproject.toml
PyPIqtpy*pyproject.toml
PyPIscikit-image*pyproject.toml
PyPIscikit-learn*pyproject.toml
PyPIseaborn*pyproject.toml
PyPIumap-learn*pyproject.toml
PyPIzarr>=3pyproject.toml
PyPItifffile*pyproject.toml
PyPIsvglib*pyproject.toml
PyPIpypdf2*pyproject.toml
PyPIimagecodecs*pyproject.toml
PyPIopencv-python*pyproject.toml
All dependencies 141

Full resolved dependency set from the GitHub dependency graph: 25 direct and 116 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIcellcutter0.2.13direct
PyPIhdbscan0.8.44direct
PyPIimagecodecs2026.3.6direct
PyPIjoblib1.5.3direct
PyPImagicgui0.10.2direct
PyPImatplotlib3.11.1direct
PyPInapari0.9.0direct
PyPInatsort8.4.0direct
PyPInumba0.67.0direct
PyPInumpy2.4.6direct
PyPIopencv-python5.0.0.93direct
PyPIpandas3.0.5direct
PyPIpyarrow25.0.1direct
PyPIpypdf23.0.1direct
PyPIpyqt66.11.0direct
PyPIpyqt6-qt66.11.2direct
PyPIpyyaml6.0.3direct
PyPIqtpy2.4.3direct
PyPIscikit-image0.26.0direct
PyPIscikit-learn1.9.0direct
PyPIseaborn0.13.2direct
PyPIsvglib2.2.0direct
PyPItifffile2026.3.3direct
PyPIumap-learn0.5.12direct
PyPIzarr3.1.6direct
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIapp-model0.5.1indirect
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PyPIattrs26.1.0indirect
PyPIbuild1.6.0indirect
PyPIcachey0.2.1indirect
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PyPIimageio2.37.4indirect
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PyPIipython9.17.0indirect
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PyPIjedi0.20.0indirect
PyPIjsonschema4.26.0indirect
PyPIjsonschema-specifications2025.9.1indirect
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PyPIpydantic-settings2.15.0indirect
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PyPIpyopengl3.1.10indirect
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PyPIpyproject-hooks1.2.0indirect
PyPIpyqt6-sip13.12.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-dotenv1.2.3indirect
PyPIpywin32312indirect
PyPIpyzmq27.2.0indirect
PyPIqtconsole5.7.2indirect
PyPIreferencing0.37.0indirect
PyPIreportlab5.0.1indirect
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PyPIwrapt2.3.0indirect
PyPIzipp4.1.0indirect
Dependency advisories 3

This repository publishes no package the index resolves, so its own dependency graph was assessed — 141 packages, which also include development and test pins that never ship: 3 carry known advisories, of which 1 are direct.

PackageVersionRelationSeverityAdvisoriesFixed in
tornado6.5.8indirecthigh36.5.9
urllib32.7.0indirecthigh62.8.0
pypdf23.0.1directmoderate23.9.0

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 v0.34.0 — full methodology · metrics wiki.

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