Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 16:18 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 62 out of 100, placing it in the Moderate band. It scores highest on Vitality (73/100) and lowest on Community & Adoption (31/100). It was last updated 19 days ago. 2 contributors account for most of its recent work.

62
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.

62
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 58 is calibrated to 62 on the published index scale (record calibration 2026-08-02).

Ownership

OpenProtein.AIOrganization
25 followers7 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-python0.17.0-6619 days ago

Metrics by category

Vitality

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

73Good · 21% of overall
How it's scored
28.8/36Push recency — last push 19 days ago
10.4/36Commit cadence — 15/52 weeks with commits
13.1/18Commit volume — 28 commits in the last year
9/10OpenSSF Scorecard: Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
Inputs used
commits_last_year28
human_commit_share0.98
days_since_last_push19
active_weeks_last_year15
How it's scored
27/27Ships releases — 43 releases published
36/36Release recency — latest release 19 days ago
27/27Release cadence — a release every ~17.3 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count43
latest_release_tagv0.17.0
releases_from_tagsno
days_since_latest_release19
mean_days_between_releases17.3

Community & Adoption

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

31At Risk · 17% of overall
How it's scored
19.5/60Stars — 17 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars17
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5License — 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_servicesbadge.fury.io
has_pull_request_templateno

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
25.2/54Bus factor — 2 contributor(s) cover half of all commits
11.7/22.5Commit distribution — top contributor authored 48% of commits
5.4/13.5Contributor breadth — 4 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor2
contributors_sampled4
top_contributor_share0.48
How it's scored
31.5/42Issue resolution — 75% of issues closed
26.7/30PR acceptance — 8/9 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/28 approved changesets -- score normalized to 0
Inputs used
merged_prs8
open_issues1
closed_issues3
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.75
closed_unmerged_prs1
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
10.2/25Owner reach — 25 followers of OpenProteinAI
16.5/25Track record — 7 public repos, account ~4 yr old
Inputs used
followers25
owner_typeOrganization
is_verifiedno
owner_loginOpenProteinAI
public_repos7
account_age_days1,815

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 19 days ago
20/20Version history — 66 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesopenprotein-python
ecosystemspypi
any_deprecatedno
min_days_since_publish19

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.black], [tool.isort])
0/9.6Pre-commit hooks
0/6.4.editorconfig
2/20OpenSSF Scorecard: CI-Tests — 1 out of 7 merged PRs checked by a CI test -- score normalized to 1
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage site — https://openprotein.ai
10/10Repository description
10/10Topics — 7 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?

48Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
0.2/2.5CI-Tests — 1 out of 7 merged PRs checked by a CI test -- score normalized to 1
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/28 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5License — license file detected
6.8/7.5Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
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
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 81 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate3.5

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages18
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:openprotein-python@0.17.0 runtime dependency closure — what installing the published package pulls in — 18 packages. 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.

42Weak · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
9.3/40Legible commit history — 17 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.173
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — mise.toml
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.black], [tool.isort])
0/11Static type checking
10/10Reproducible environment — Nix, lockfile
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 — dependency 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_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
55/55Manageable file sizes — 0/214 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes46,133
source_files_sampled214
oversized_source_files0

Key facts

17GitHub stars
4contributors
28commits, last 12 months
19days since last push
43releases
2bus factor
1open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'openprotein-python' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

More detail

OpenSSF Scorecard 3.5 / 10
3.5aggregate

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 · 2026-09-10 16:18 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
1CI-Tests1 out of 7 merged PRs checked by a CI test -- score normalized to 1
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/28 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
9Maintained11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
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
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
0Vulnerabilities81 existing vulnerabilities detected
Direct dependencies 8
RegistryPackageVersion constraintManifest
PyPIrequests>=2.32.3pyproject.toml
PyPIpydantic>=2.5pyproject.toml
PyPItqdm>=4.66.4pyproject.toml
PyPIpandas>=2.2.2pyproject.toml
PyPInumpy>=1.9pyproject.toml
PyPIgemmi>=0.6.0,<0.8pyproject.toml
PyPItomli>=2.3.0pyproject.toml
PyPIfilelock>=3.13pyproject.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

Dependency advisories 0

Installing pypi:openprotein-python@0.17.0 pulls in 18 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

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.