Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-03 05:49 UTC

starsimhub / starsim

Starsim disease modeling framework

PythonMIT★ 44 stars⑂ 32 forkssince May 2023View on GitHub ↗

starsimhub/starsim holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Vitality (95/100) and lowest on AI Readiness (57/100). It was last updated today. A single contributor accounts for most of its recent work.

91
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.

91
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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

StarsimHubOrganization
35 followers60 public repossince Nov 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIstarsim3.7.02,068440 days agoagent-based-modelsimulationdiseaseepidemiology

Metrics by category

Vitality

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

95Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
27/36Commit cadence — 39/52 weeks with commits
18/18Commit volume — 796 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year796
human_commit_share1
days_since_last_push0
active_weeks_last_year39

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 22 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~18.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count22
latest_release_tagv3.7.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases18.9
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?

64Moderate · 17% of overall
How it's scored
26.5/60Stars — 44 stars
12.4/25Forks — 32 forks
6.2/15Watchers — 14 watchers
Inputs used
forks32
stars44
watchers14
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadgen.net, github.com
has_pull_request_templateyes
How it's scored
44.2/80Monthly downloads — 2,068 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesstarsim
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,068
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?

65Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
8.4/22.5Commit distribution — top contributor authored 62% of commits
13.5/13.5Contributor breadth — 25 contributors
10/10OpenSSF Scorecard: Contributors — project has 20 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled25
top_contributor_share0.625
How it's scored
35.1/42Issue resolution — 84% of issues closed
25.4/30PR acceptance — 388/458 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/1 approved changesets -- score normalized to 0
Inputs used
merged_prs388
open_issues157
closed_issues792
prs_merged_7d2
prs_decided_7d2
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0.835
closed_unmerged_prs70
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
11.2/25Owner reach — 35 followers of starsimhub
20.7/25Track record — 60 public repos, account ~3 yr old
Inputs used
followers35
owner_typeOrganization
is_verifiedno
owner_loginstarsimhub
public_repos60
account_age_days1,409

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 44 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesstarsim
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows — 9 workflow(s)
24/24Tests present
16/16Linter config — .flake8, .pylintrc
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 1 out of 1 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://starsim.org
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsstarsim, agent-based-modeling, public-health, simulation
has_wikiyes
homepagehttp://starsim.org
docs_sitehttp://starsim.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

71Good · 16% of overall
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 — 1 out of 1 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
0/7.5Code-Review — Found 0/1 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 20 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
7.5/7.5Maintained — 30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
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
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.4
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
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages42
unassessed_packages17
affected_by_severitynone
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 42 resolved dependencies against OSV. 17 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. 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.

57Moderate · 4% of overall
How it's scored
45/45Agent instructions — CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt present
2.1/40Legible commit history — 4 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_url—
legible_history_share0.04
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes6,615
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — .flake8, .pylintrc
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0
How it's scored
0/45Type-checkable code — Python without a type-check config
53.6/55Manageable file sizes — 3/115 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes107,615
source_files_sampled115
oversized_source_files3
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 — examples
Inputs used
example_dirsexamples
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

44GitHub stars
25contributors
796commits, last 12 months
0days since last push
22releases
1bus factor
157open 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:starsim@3.7.0; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 32 ⇿
0Stars
32Forks
20Releases

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.

01325383122024-042025-072026-09
Major 0Minor 6Patch 14

Each point covers 3 days.

OpenSSF Scorecard 6.4 / 10
6.4aggregate

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 · 2026-10-03 05:49 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-Tests1 out of 1 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/1 approved changesets -- score normalized to 0
10Contributorsproject has 20 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
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
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
PyPInumpy>=2.0.0pyproject.toml
PyPIpandas>=2.1.0pyproject.toml
PyPIsciris>=3.2.8pyproject.toml
PyPInumba>=0.57.0pyproject.toml
PyPIscipy—pyproject.toml
PyPInetworkx—pyproject.toml
PyPImatplotlib—pyproject.toml
PyPIseaborn—pyproject.toml
PyPIoptuna—pyproject.toml
All dependencies 59

Full resolved dependency set from the GitHub dependency graph: 18 direct and 41 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPImatplotlib—direct
PyPImatplotlib3.11.2direct
PyPInetworkx—direct
PyPInetworkx3.7direct
PyPInumba—direct
PyPInumba0.68.0direct
PyPInumpy—direct
PyPInumpy2.5.3direct
PyPIoptuna—direct
PyPIoptuna5.0.0direct
PyPIpandas—direct
PyPIpandas3.0.6direct
PyPIscipy—direct
PyPIscipy1.18.1direct
PyPIsciris—direct
PyPIsciris3.4.0direct
PyPIseaborn—direct
PyPIseaborn0.13.2direct
PyPIalembic1.20.0indirect
PyPIcolorlog6.12.0indirect
PyPIcontourpy1.4.0indirect
PyPIcycler0.12.1indirect
PyPIdask—indirect
PyPIdill0.4.1indirect
PyPIdistribute—indirect
PyPIet-xmlfile2.0.0indirect
PyPIfonttools4.66.1indirect
PyPIgitdb4.0.12indirect
PyPIgitpython3.2.0indirect
PyPIjellyfish1.2.1indirect
PyPIjsonpickle4.1.2indirect
PyPIjupyter—indirect
PyPIjupyter-cache—indirect
PyPIjupytext—indirect
PyPIkiwisolver1.5.1indirect
PyPIline-profiler5.0.2indirect
PyPIllvmlite0.50.0indirect
PyPImako1.4.3indirect
PyPImarkupsafe3.0.3indirect
PyPImemory-profiler0.61.0indirect
PyPImultiprocess0.70.19indirect
PyPIopenpyxl3.1.5indirect
PyPIpackaging26.3indirect
PyPIpillow12.3.0indirect
PyPIpsutil7.2.2indirect
PyPIpyparsing3.3.3indirect
PyPIpytest—indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpyyaml6.0.3indirect
PyPIquartodoc—indirect
PyPIsetuptools84.0.0indirect
PyPIsix1.17.0indirect
PyPIsmmap5.0.3indirect
PyPIsphobjinv—indirect
PyPIsqlalchemy2.1.1indirect
PyPItqdm4.70.1indirect
PyPItyping-extensions4.16.0indirect
PyPIxlsxwriter3.2.9indirect
PyPIzstandard0.25.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 42 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 17 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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.

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.