Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-08 15:12 UTC

tilde-lab / pycrystal

Utilities for ab initio modeling suite CRYSTAL, developed in Turin University

PythonCustom license★ 11 stars⑂ 1 forksince Dec 2018View on GitHub ↗

tilde-lab/pycrystal holds a health index of 24 out of 100, placing it in the At Risk band. It scores highest on Sustainability & Governance (55/100) and lowest on Vitality (18/100). It was last updated 375 days ago. A single contributor accounts for most of its recent work.

24
overall / 100
At Risk

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.

24
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 34 is calibrated to 28 on the published index scale (record calibration 2026-08-02).

Ownership

TildeOrganization · verified domain
60 followers33 public repossince Mar 2015

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

Package ecosystems

Metrics by category

Vitality

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

18Critical · 21% of overall
How it's scored
0/36Push recency — last push 375 days ago
0/36Commit cadence — 0/52 weeks with commits
0/18Commit volume — 0 commits in the last year
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.98
days_since_last_push375
active_weeks_last_year0
How it's scored
27/27Ships releases — 1 releases published
0/36Release recency — latest release 1,285 days ago
12.6/27Release cadence — cadence unknown (single release)
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count1
latest_release_tagv1.0.16
releases_from_tagsno
days_since_latest_release1,285
mean_days_between_releases—
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?

32At Risk · 17% of overall
How it's scored
16.2/60Stars — 11 stars
0/25Forks — 1 forks
0/15Watchers — 1 watchers
Inputs used
forks1
stars11
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — license 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_badges1
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno
How it's scored
31.3/80Monthly downloads — 223 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespycrystal
dependents—
ecosystemspypi
total_downloads—
monthly_downloads223
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?

55Moderate · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
5/22.5Commit distribution — top contributor authored 78% of commits
4.1/13.5Contributor breadth — 3 contributors
10/10OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.777
How it's scored
19.1/42Issue resolution — 46% of issues closed
3.3/30PR acceptance — 2/18 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 2/28 approved changesets -- score normalized to 0
Inputs used
merged_prs2
open_issues6
closed_issues5
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.455
closed_unmerged_prs16
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
20/20Verified domain
12.8/25Owner reach — 60 followers of tilde-lab
23.2/25Track record — 33 public repos, account ~11 yr old
Inputs used
followers60
owner_typeOrganization
is_verifiedyes
owner_logintilde-lab
public_repos33
account_age_days4,197
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
26/35Publish recency — latest publish 264 days ago
20/20Version history — 14 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespycrystal
ecosystemspypi
any_deprecatedno
min_days_since_publish264

Engineering Quality

Are baseline engineering and documentation practices in place?

34At Risk · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 2 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 14 topics
0/10Wiki
Inputs used
topicsabinitio, abinitio-simulations, crystal-structure, crystal, first-principles, materials-science, crystallography, crystal-ab-initio, gaussian, gaussian-lcao, emsl, computational-chemistry, computational-materials, atomistic-simulations
has_wikino
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?

28At Risk · 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 2 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 2/28 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 9 contributing companies or organizations
0/10Dangerous-Workflow — no data
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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_aggregate2.8
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. 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.

21At Risk · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
2.7/40Legible commit history — 5 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.051
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configno
typecheck_configs—
agent_commit_share0
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
50.4/55Manageable file sizes — 1/12 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes75,601
source_files_sampled12
oversized_source_files1

Key facts

11GitHub stars
3contributors
0commits, last 12 months
375days since last push
1releases
1bus factor
6open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • No resolved dependencies carried a version and a supported ecosystem

More detail

OpenSSF Scorecard 2.8 / 10
2.8aggregate

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 · 2026-09-08 15:12 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 2 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 2/28 approved changesets -- score normalized to 0
10Contributorsproject has 9 contributing companies or organizations
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
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
All dependencies 7

Full resolved dependency set from the GitHub dependency graph: 0 direct and 7 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIase—indirect
PyPIbeautifulsoup4—indirect
PyPIbs4—indirect
PyPInumpy—indirect
PyPIpyparsing—indirect
PyPIrequests—indirect
PyPIscipy—indirect
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 v0.34.0 — full methodology · metrics wiki.

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