Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 05:11 UTC

vprusso / toqito

|toqito> (Theory of Quantum Information Toolkit) is a Python library for research in quantum information theory.

PythonMIT★ 287 stars⑂ 165 forkssince Jan 2020View on GitHub ↗
KindLibraryhow this is determined
#quantum-computing#python#quantum-information#matrix-analysis#python-3#physics#quantum#convex-optimization#linear-algebra#quantum-information-science#quantum-information-theory#quantum-physics#quantum-programming#research#nonlocal-game#semidefinite-programming#entanglement#quantum-channels#quantum-measurements#quantum-states

vprusso/toqito holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Vitality (96/100) and lowest on AI Readiness (45/100). It was last updated today. A single contributor accounts for most of its recent work.

92
overall / 100
Excellent

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.

92
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 78 is calibrated to 92 on the published index scale (record calibration 2026-08-02).

Ownership

Vincent RussoPersonal account
798 followers79 public repossince Mar 2012

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
PyPItoqito1.3.0-263 days agoquantum-informationquantum-information-theoryquantum-computingquantum-statesquantum-channelsquantum-measurementsentanglementdensity-matricesnonlocal-gamessemidefinite-programmingcvxpynumpy

Metrics by category

Vitality

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

96Exceptional · 21% of overall

Development activity

98Exceptional
How it's scored
36/36Push recency — last push 0 days ago
33.9/36Commit cadence — 49/52 weeks with commits
18/18Commit volume — 808 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year808
human_commit_share—
days_since_last_push0
active_weeks_last_year49

Release discipline

92Excellent
How it's scored
27/27Ships releases — 20 releases published
36/36Release recency — latest release 3 days ago
19.8/27Release cadence — a release every ~62.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count20
latest_release_tagv1.3.0
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases62.2
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?

70Good · 17% of overall

Popularity & adoption

64Moderate
How it's scored
39.8/60Stars — 287 stars
18.5/25Forks — 165 forks
5.3/15Watchers — 10 watchers
Inputs used
forks165
stars287
watchers10
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code 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_conductno
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

73Good · 23% of overall

Maintainer resilience (bus factor)

42Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
9.4/22.5Commit distribution — top contributor authored 58% of commits
13.5/13.5Contributor breadth — 79 contributors
10/10OpenSSF Scorecard: Contributors — project has 15 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled79
top_contributor_share0.584

Issue & PR responsiveness

90Excellent
How it's scored
41.9/42Issue resolution — 100% of issues closed
26.2/30PR acceptance — 1,117/1,277 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-Review — Found 20/28 approved changesets -- score normalized to 7
Inputs used
merged_prs1,117
open_issues2
closed_issues588
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.997
closed_unmerged_prs160
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.

Ownership & stewardship

70Good
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
20.9/25Owner reach — 798 followers of vprusso
25/25Track record — 79 public repos, account ~14 yr old
Inputs used
followers798
owner_typeUser
is_verified—
owner_loginvprusso
public_repos79
account_age_days5,230
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 3 days ago
20/20Version history — 26 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagestoqito
ecosystemspypi
any_deprecatedno
min_days_since_publish3

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://vprusso.github.io/toqito/
10/10Repository description
10/10Topics — 20 topics
10/10Wiki
Inputs used
topicsquantum-computing, python, quantum-information, matrix-analysis, python-3, physics, quantum, convex-optimization, linear-algebra, quantum-information-science, quantum-information-theory, quantum-physics, quantum-programming, research, nonlocal-game, semidefinite-programming, entanglement, quantum-channels, quantum-measurements, quantum-states
has_wikiyes
homepagehttps://vprusso.github.io/toqito/
docs_sitehttps://vprusso.github.io/toqito/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

55Moderate · 16% of overall

Security posture

55Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.2/2.5CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-Review — Found 20/28 approved changesets -- score normalized to 7
2.5/2.5Contributors — project has 15 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
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 — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 10 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.6
Excluded from scoring (no data or not applicable): Branch-Protection, 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.

45Weak · 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)

53Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.8/55Manageable file sizes — 2/555 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes71,898
source_files_sampled555
oversized_source_files2

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples
Inputs used
example_dirsexamples
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

287GitHub stars
79contributors
808commits, last 12 months
0days since last push
20releases
1bus factor
2open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 5.6 / 10
5.6aggregate

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 · 2026-07-17 05:10 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
9CI-Tests29 out of 30 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 20/28 approved changesets -- score normalized to 7
10Contributorsproject has 15 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 29 issue activity found in the last 90 days -- score normalized to 10
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
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities10 existing vulnerabilities detected
Direct dependencies 8
RegistryPackageVersion constraintManifest
PyPIcvxpy>=1.9.0,<2pyproject.toml
PyPImore-itertools>=11.1.0,<12pyproject.toml
PyPInumpy>=2.4.1,<3pyproject.toml
PyPIscipy>=1.17.1,<2pyproject.toml
PyPIscs>=3.2.11,<4pyproject.toml
PyPIpicos>=2.6.2pyproject.toml
PyPInetworkx>=3.4,<4.0pyproject.toml
PyPImatplotlib>=3.11.0,<4pyproject.toml
All dependencies 136

Full resolved dependency set from the GitHub dependency graph: 8 direct and 128 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPImatplotlib3.11.0direct
PyPImore-itertools11.1.0direct
PyPInetworkx3.5direct
PyPInumpy2.4.1direct
PyPIpicos2.6.2direct
PyPIscipy1.17.1direct
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PyPIcertifi2025.8.3indirect
PyPIcffi2.0.0indirect
PyPIcfgv3.4.0indirect
PyPIcharset-normalizer3.4.3indirect
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PyPIplatformdirs4.4.0indirect
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PyPIpytest9.1.0indirect
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PyPIsparsediffpy0.3.0indirect
PyPIstack-data0.6.3indirect
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PyPItoqito1.2.0indirect
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PyPItqdm4.67.3indirect
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PyPIty0.0.12indirect
PyPItyping-extensions4.15.0indirect
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Raw JSON report machine-readable

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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.