Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-15 11:24 UTC

mooreneural / proteintensor

AI-native tensor format (.ptt) for protein-structure ML. Convert a structure or sequence once; load backbone, MSA, ESM embeddings, sparse pair features, and ligands with zero parsing. Feeds AlphaFold/Boltz (Boltz-2 verified). Zarr-backed, lossless, PyTorch/JAX-ready, streams from S3/GCS.

PythonMIT★ 1 star⑂ 0 forkssince Jun 2026View on GitHub ↗
KindLibraryCommand-line toolhow this is determined
#computational-biology#protein-language-model#tensor-format

mooreneural/proteintensor holds a health index of 53 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (76/100) and lowest on AI Readiness (23/100). It was last updated 5 days ago. A single contributor accounts for most of its recent work.

53
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.

53
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 52 is calibrated to 53 on the published index scale (record calibration 2026-08-02).

Ownership

Clay MoorePersonal account
3 followers21 public repossince Mar 2024Texas A&M University

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIproteintensor0.4.0-46 days agoprotein-structurestructural-biologymachine-learningtensorzarralphafoldboltz

Metrics by category

Vitality

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

73Good · 21% of overall

Development activity

55Moderate
How it's scored
36/36Push recency — last push 5 days ago
3.5/36Commit cadence — 5/52 weeks with commits
15.8/18Commit volume — 57 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year57
human_commit_share—
days_since_last_push5
active_weeks_last_year5

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 4 releases published
36/36Release recency — latest release 6 days ago
27/27Release cadence — a release every ~11.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count4
latest_release_tagv0.4.0
releases_from_tagsno
days_since_latest_release6
mean_days_between_releases11.6
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?

43Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars1
watchers0
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_badges—
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

32At Risk · 23% of overall

Maintainer resilience (bus factor)

13Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — no decided pull requests or no data
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

36Weak
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
4.3/25Owner reach — 3 followers of mooreneural
14.4/25Track record — 21 public repos, account ~2 yr old
Inputs used
followers3
owner_typeUser
is_verified—
owner_loginmooreneural
public_repos21
account_age_days842
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

92Excellent
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 6 days ago
12/20Version history — 4 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesproteintensor
ecosystemspypi
any_deprecatedno
min_days_since_publish6

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall

Engineering practices

60Moderate
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no 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 site — https://zenodo.org/records/21266859
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicscomputational-biology, protein-language-model, tensor-format
has_wikiyes
homepagehttps://zenodo.org/records/21266859
docs_sitehttps://zenodo.org/records/21266859
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

40Weak · 16% of overall

Security posture

40Weak
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 — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
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_aggregate4
Excluded from scoring (no data or not applicable): 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.

23At Risk · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no 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.

Verify loop (build / test / typecheck)

27At Risk
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 data
0/8Automated maintenance — no data
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_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.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/43 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes21,315
source_files_sampled43
oversized_source_files0

Key facts

1GitHub stars
1contributors
57commits, last 12 months
5days since last push
4releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

OpenSSF Scorecard 4.0 / 10
4.0aggregate

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 · 2026-07-15 11:24 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
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
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 6
RegistryPackageVersion constraintManifest
PyPIzarr>=2.18,<3pyproject.toml
PyPInumcodecs>=0.12pyproject.toml
PyPInumpy>=1.24pyproject.toml
PyPIgemmi>=0.6pyproject.toml
PyPIclick>=8.1pyproject.toml
PyPIrich>=13pyproject.toml
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Raw JSON report machine-readable

Feedback

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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 v0.11.0 — full methodology · metrics wiki.

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