Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-13 13:21 UTC

marcelwa / aigverse

A Python library for working with logic networks, synthesis, and optimization.

Python · C++MIT★ 90 stars⑂ 6 forkssince Sep 2024View on GitHub ↗
KindLibraryhow this is determined
#aig#aiger#machine-learning#logic-optimization#logic-synthesis#python#verilog

marcelwa/aigverse holds a health index of 92 out of 100, placing it in the Excellent band. It scores highest on Vitality (98/100) and lowest on Community & Adoption (58/100). 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

Marcel WalterPersonal account
43 followers24 public repossince Jun 2016@cda-tum and @munich-quantum-software

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
PyPIaigverse0.1.64,529330 days agoaigaigverseartificial-intelligenceedalogicmachine-learningoptimizationsynthesis

Metrics by category

Vitality

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

98Exceptional · 21% of overall

Development activity

97Exceptional
How it's scored
36/36Push recency — last push 0 days ago
33.2/36Commit cadence — 48/52 weeks with commits
18/18Commit volume — 285 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year285
human_commit_share0.33
days_since_last_push0
active_weeks_last_year48

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 34 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~39.7 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count34
latest_release_tagv0.1.6
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases39.7
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?

58Moderate · 17% of overall

Popularity & adoption

40Weak
How it's scored
31.6/60Stars — 90 stars
5.8/25Forks — 6 forks
2.7/15Watchers — 4 watchers
Inputs used
forks6
stars90
watchers4
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_badges7
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

61Moderate
How it's scored
48.7/80Monthly downloads — 4,529 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesaigverse
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4,529
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?

59Moderate · 23% of overall

Maintainer resilience (bus factor)

24At Risk
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0.8/22.5Commit distribution — top contributor authored 97% of commits
4.1/13.5Contributor breadth — 3 contributors
10/10OpenSSF Scorecard: Contributors — project has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled3
top_contributor_share0.966

Issue & PR responsiveness

71Good
How it's scored
33.6/42Issue resolution — 80% of issues closed
28.1/30PR acceptance — 480/512 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/24 approved changesets -- score normalized to 0
Inputs used
merged_prs480
open_issues8
closed_issues32
prs_merged_7d3
prs_decided_7d3
prs_merged_30d8
prs_decided_30d8
issue_closed_ratio0.8
closed_unmerged_prs32
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.

Ownership & stewardship

55Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
11.8/25Owner reach — 43 followers of marcelwa
22.2/25Track record — 24 public repos, account ~10 yr old
Inputs used
followers43
owner_typeUser
is_verified—
owner_loginmarcelwa
public_repos24
account_age_days3,773
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 0 days ago
20/20Version history — 33 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesaigverse
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

92Excellent · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 15 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://aigverse.readthedocs.io/
10/10Repository description
10/10Topics — 7 topics
0/10Wiki
Inputs used
topicsaig, aiger, machine-learning, logic-optimization, logic-synthesis, python, verilog
has_wikino
homepagehttps://aigverse.readthedocs.io/
docs_sitehttps://aigverse.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

82Excellent · 16% of overall

Security posture

78Good
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/24 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 3 contributing companies or organizations -- score normalized to 10
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 18 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
4/5SAST — SAST tool detected but not run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7.8
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages175
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 175 resolved dependencies against OSV. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

97Exceptional · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://aigverse.readthedocs.io/llms.txt)
40/40Legible commit history — 33 of 33 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://aigverse.readthedocs.io/llms.txt
legible_history_share1
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes14,008

Verify loop (build / test / typecheck)

99Exceptional
How it's scored
18/18One-command bootstrap — noxfile.py
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — python/aigverse/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 67 of the last 100 commits are automated dependency updates
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesnoxfile.py
has_devcontainerno
has_linter_configyes
typecheck_configspython/aigverse/py.typed
agent_commit_share0.06
toolchain_manifests—
dependency_bot_commit_share0.67

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (python/aigverse/py.typed)
55/55Manageable file sizes — 0/104 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes53,874
source_files_sampled104
oversized_source_files0

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

90GitHub stars
3contributors
285commits, last 12 months
0days since last push
34releases
1bus factor
8open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:aigverse@0.1.6; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 6 ⇿
0Stars
6Forks
13Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

123456612025-042025-112026-05
Major 0Minor 1Patch 12

Each point covers 2 days.

OpenSSF Scorecard 7.8 / 10
7.8aggregate

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 · 2026-10-13 13:21 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/24 approved changesets -- score normalized to 0
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
8SASTSAST tool detected but not run on all commits
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPInanobind-backend>=1.0pyproject.toml
All dependencies 175

Full resolved dependency set from the GitHub dependency graph: 1 direct and 174 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 175 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct.

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

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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 v0.34.0 — full methodology · metrics wiki.

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