Public record
Software health reportschema 0.12.0 · metrics 2.10.0 · 2026-07-18 02:56 UTC

openproteinai / openprotein-python

Simple python interface for the OpenProtein.AI REST API.

PythonCustom license★ 17 stars⑂ 0 forkssince Aug 2023View on GitHub ↗

openproteinai/openprotein-python holds a health index of 56 out of 100, placing it in the Moderate band. It scores highest on Vitality (78/100) and lowest on Security (26/100). It was last updated 2 days ago. 2 contributors account for most of its recent work.

56
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.

56
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 54 is calibrated to 56 on the published index scale (record calibration 2026-08-02).

Ownership

OpenProtein.AIOrganization
25 followers13 public repossince Sep 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIopenprotein-python0.16.0-643 days ago

Metrics by category

Vitality

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

78Good · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
13.8/36Commit cadence20/52 weeks with commits
13.4/18Commit volume30 commits in the last year
7/10OpenSSF Scorecard: Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
Inputs used
commits_last_year30
human_commit_share
days_since_last_push2
active_weeks_last_year20
How it's scored
27/27Ships releases41 releases published
36/36Release recencylatest release 3 days ago
27/27Release cadencea release every ~14.6 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count41
latest_release_tagv0.16.0
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases14.6

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

31At Risk · 17% of overall
How it's scored
19.5/60Stars17 stars
0/25Forks0 forks
0/15Watchers1 watchers
Inputs used
forks0
stars17
watchers1
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?

68Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
12.2/22.5Commit distributiontop contributor authored 46% of commits
5.4/13.5Contributor breadth4 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor2
contributors_sampled4
top_contributor_share0.459
How it's scored
31.5/42Issue resolution75% of issues closed
20/30PR acceptance2/3 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_prs2
open_issues1
closed_issues3
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.75
closed_unmerged_prs1
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
10.2/25Owner reach25 followers of OpenProteinAI
18/25Track record13 public repos, account ~4 yr old
Inputs used
followers25
owner_typeOrganization
is_verified
owner_loginOpenProteinAI
public_repos13
account_age_days1,760
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 3 days ago
20/20Version history64 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesopenprotein-python
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

59Moderate · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://openprotein.ai
10/10Repository description
10/10Topics7 topics
10/10Wiki
Inputs used
topicsgenerative-ai, language-model, machine-learning, protein-embedding, protein-language-model, proteins, python
has_wikiyes
homepagehttps://openprotein.ai
docs_sitehttps://openprotein.ai
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

26At Risk · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 1 merged PRs checked by a CI test -- score normalized to 0
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
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
5.2/7.5Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities68 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate2.6
Excluded from scoring (no data or not applicable): Packaging. 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.

39Weak · 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 bootstrapmise.toml
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentNix, lockfile
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_nixyes
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesmise.toml
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
55/55Manageable file sizes0/212 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes45,618
source_files_sampled212
oversized_source_files0

Key facts

17GitHub stars
4contributors
30commits, last 12 months
2days since last push
41releases
2bus factor
1open 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 2.6 / 10
2.6aggregate

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 · 2026-07-18 02:56 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 1 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 0/30 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
7Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities68 existing vulnerabilities detected
Direct dependencies 8
RegistryPackageVersion constraintManifest
PyPIrequests>=2.32.3,<3pyproject.toml
PyPIpydantic>=2.5,<3pyproject.toml
PyPItqdm>=4.66.4,<5pyproject.toml
PyPIpandas>=2.2.2,<3pyproject.toml
PyPInumpy>=1.9,<3pyproject.toml
PyPIgemmi>=0.6.0,<0.8pyproject.toml
PyPItomli>=2.3.0,<3pyproject.toml
PyPIfilelock>=3.13,<4pyproject.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

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 v0.12.0 — full methodology · metrics wiki.

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