Public record
Software health reportschema 0.16.0 · metrics 2.10.0 · 2026-07-21 00:20 UTC

GalSim-developers / GalSim

The modular galaxy image simulation toolkit. Documentation:

Python · C++Custom license★ 271 stars⑂ 119 forkssince Feb 2012View on GitHub ↗

GalSim-developers/GalSim holds a health index of 60 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (76/100) and lowest on Security (21/100). It was last updated 53 days ago. 2 contributors account for most of its recent work.

60
overall / 100
Moderate

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.

60
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 57 is calibrated to 60 on the published index scale (record calibration 2026-08-02).

Ownership

GalSim-developersOrganization
17 followers4 public repossince Feb 2012

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

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 recencylast push 53 days ago
5.5/36Commit cadence8/52 weeks with commits
17.6/18Commit volume89 commits in the last year
2/10OpenSSF Scorecard: Maintained0 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 2
Inputs used
commits_last_year89
human_commit_share
days_since_last_push53
active_weeks_last_year8
How it's scored
27/27Ships releases34 releases published
27/36Release recencylatest release 148 days ago
19.8/27Release cadencea release every ~49.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count34
latest_release_tagv2.8.4
releases_from_tagsno
days_since_latest_release148
mean_days_between_releases49.7
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?

56Moderate · 17% of overall
How it's scored
39.4/60Stars271 stars
17.3/25Forks119 forks
8.8/15Watchers39 watchers
Inputs used
forks119
stars271
watchers39
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

69Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.9/22.5Commit distributiontop contributor authored 47% of commits
13.5/13.5Contributor breadth49 contributors
10/10OpenSSF Scorecard: Contributorsproject has 49 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled49
top_contributor_share0.469
How it's scored
40.8/42Issue resolution97% of issues closed
28.3/30PR acceptance533/566 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs533
open_issues22
closed_issues771
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.972
closed_unmerged_prs33
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.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
9/25Owner reach17 followers of GalSim-developers
17.1/25Track record4 public repos, account ~14 yr old
Inputs used
followers17
owner_typeOrganization
is_verified
owner_loginGalSim-developers
public_repos4
account_age_days5,262
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttp://galsim-developers.github.io/GalSim/
10/10Repository description
10/10Topics11 topics
10/10Wiki
Inputs used
topicspython, c-plus-plus, astronomy, galaxy, simulation, simulate-images, weaklensing, lsst, des, wfirst, euclid
has_wikiyes
homepagehttp://galsim-developers.github.io/GalSim/
docs_sitehttp://galsim-developers.github.io/GalSim/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

21At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 49 contributing companies or organizations
0/10Dangerous-Workflowdangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
1.5/7.5Maintained0 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 2
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities20 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate2.1
Excluded from scoring (no data or not applicable): Branch-Protection, CI-Tests, Signed-Releases. Remaining weights renormalized.

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.

43Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrapdocs/Makefile, include/galsim/fmath/Makefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile, include/galsim/fmath/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
51.2/55Manageable file sizes39/567 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes594,665
source_files_sampled567
oversized_source_files39
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
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

271GitHub stars
49contributors
89commits, last 12 months
53days since last push
34releases
2bus factor
22open issues
PyPIpackage ecosystems

Data collection warnings

  • Could not fetch pypi package 'libfftw3' from its registry
  • No resolved dependencies carried a version and a supported ecosystem

More detail

OpenSSF Scorecard 2.1 / 10
2.1aggregate

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 · 2026-07-21 00:19 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
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
10Contributorsproject has 49 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
2Maintained0 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 2
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities20 existing vulnerabilities detected
All dependencies 15

Full resolved dependency set from the GitHub dependency graph: 0 direct and 15 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIastropyindirect
PyPIeigenindirect
PyPIfftwindirect
PyPIlsstdesc-coordindirect
PyPImatplotlibindirect
PyPInumpyindirect
PyPIpandasindirect
PyPIpipindirect
PyPIpybind11indirect
PyPIpytestindirect
PyPIpytest-timeoutindirect
PyPIpytest-xdistindirect
PyPIpyyamlindirect
PyPIscipyindirect
PyPIsetuptoolsindirect
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies carried a version and a supported ecosystem

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 v0.16.0 — full methodology · metrics wiki.

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