Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-14 03:26 UTC

gianlucamazza / mklang

A declarative language for LLM-driven state machines - the .mkl document is the program, an LLM is the runtime

PythonApache-2.0★ 1 star⑂ 0 forkssince Jul 2026View on GitHub ↗
KindPluginCommand-line toolLibraryTerminal interfacehow this is determined
#agents#dsl#llm#python#state-machine

gianlucamazza/mklang holds a health index of 81 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (100/100) and lowest on Community & Adoption (42/100). It was last updated today. A single contributor accounts for most of its recent work.

81
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.

81
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 69 is calibrated to 81 on the published index scale (record calibration 2026-08-02).

Ownership

Gianluca MazzaPersonal account
74 followers78 public repossince Jan 2017gianlucamazza

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
PyPImklang1.3.52,678367 days agoagentsdslllmreasoningstate-machine

Metrics by category

Vitality

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

77Good · 21% of overall

Development activity

61Moderate
How it's scored
36/36Push recency — last push 0 days ago
6.9/36Commit cadence — 10/52 weeks with commits
18/18Commit volume — 389 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_year389
human_commit_share0.93
days_since_last_push0
active_weeks_last_year10

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 41 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~4.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count41
latest_release_tagv1.3.5
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases4.5
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?

42Weak · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars1
watchers1
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 (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

57Moderate
How it's scored
45.7/80Monthly downloads — 2,678 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesmklang
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,678
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)

19Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
1.3/22.5Commit distribution — top contributor authored 94% of commits
2.7/13.5Contributor breadth — 2 contributors
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.944

Issue & PR responsiveness

74Good
How it's scored
36/42Issue resolution — 86% of issues closed
28/30PR acceptance — 84/90 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/29 approved changesets -- score normalized to 0
Inputs used
merged_prs84
open_issues2
closed_issues12
prs_merged_7d2
prs_decided_7d2
prs_merged_30d4
prs_decided_30d4
issue_closed_ratio0.857
closed_unmerged_prs6
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

61Moderate
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
13.5/25Owner reach — 74 followers of gianlucamazza
25/25Track record — 78 public repos, account ~9 yr old
Inputs used
followers74
owner_typeUser
is_verified—
owner_logingianlucamazza
public_repos78
account_age_days3,534
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 7 days ago
20/20Version history — 36 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesmklang
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 4 out of 4 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://gianlucamazza.github.io/mklang/
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicsagents, dsl, llm, python, state-machine
has_wikiyes
homepagehttps://gianlucamazza.github.io/mklang/
docs_sitehttps://gianlucamazza.github.io/mklang/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

53Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 4 out of 4 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 0/29 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
7.5/7.5Dependency-Update-Tool — 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 — SAST tool is not run on all commits -- score normalized to 0
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_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.3
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
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_packages29
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:mklang@1.3.5 runtime dependency closure — what installing the published package pulls in — 29 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.

68Good · 4% of overall

Agent context & guidance

40Weak
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 92 of 93 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.989
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

72Good
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/mklang/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 43 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 6 of the last 100 commits are automated dependency updates
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_configssrc/mklang/py.typed
agent_commit_share0.43
toolchain_manifests—
dependency_bot_commit_share0.06

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/mklang/py.typed)
54.5/55Manageable file sizes — 1/118 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes65,922
source_files_sampled118
oversized_source_files1

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — demos, examples
Inputs used
example_dirsdemos, examples
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

1GitHub stars
2contributors
389commits, last 12 months
0days since last push
41releases
1bus factor
2open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

OpenSSF Scorecard 5.3 / 10
5.3aggregate

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 · 2026-09-14 03:26 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests4 out of 4 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 0/29 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate 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
0SASTSAST tool is not run on all commits -- score normalized to 0
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
PyPIpyyaml>=6pyproject.toml
PyPIjsonschema>=4pyproject.toml
PyPIpython-dotenv>=1pyproject.toml
PyPIopenai>=1.40pyproject.toml
PyPIrich>=13.7pyproject.toml
PyPItextual>=0.80pyproject.toml
All dependencies 89

Full resolved dependency set from the GitHub dependency graph: 6 direct and 83 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIjsonschema4.26.0direct
PyPIopenai3.1.0direct
PyPIpython-dotenv1.2.3direct
PyPIpyyaml6.0.3direct
PyPIrich15.0.0direct
PyPItextual8.2.8direct
PyPIannotated-types0.7.0indirect
PyPIanthropic0.122.0indirect
PyPIanyio4.14.1indirect
PyPIargcomplete3.7.2indirect
PyPIast-serialize0.6.0indirect
PyPIattrs26.1.0indirect
PyPIbabel2.18.0indirect
PyPIbackrefs8.0indirect
PyPIcertifi2026.6.17indirect
PyPIcffi2.1.0indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.15.2indirect
PyPIcryptography50.0.0indirect
PyPIdistro1.9.0indirect
PyPIdocstring-parser0.18.0indirect
PyPIghp-import2.1.0indirect
PyPIh110.16.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpcore22.12.0indirect
PyPIhttpx0.28.1indirect
PyPIhttpx22.12.0indirect
PyPIhttpx2-jsfetch1.0indirect
PyPIidna3.18indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIjiter0.16.0indirect
PyPIjsonschema-specifications2025.9.1indirect
PyPIlibrt0.13.0indirect
PyPIlinkify-it-py2.1.0indirect
PyPImarkdown3.10.3indirect
PyPImarkdown-it-py4.2.0indirect
PyPImarkupsafe3.0.3indirect
PyPImcp2.0.0indirect
PyPImcp-types2.0.0indirect
PyPImdit-py-plugins0.6.1indirect
PyPImdurl0.1.2indirect
PyPImergedeep1.3.4indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-material9.7.7indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImklang1.3.5indirect
PyPImypy2.3.1indirect
PyPImypy-extensions1.1.0indirect
PyPIopentelemetry-api1.44.0indirect
PyPIpackaging26.2indirect
PyPIpaginate0.5.7indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.10.0indirect
PyPIpluggy1.6.0indirect
PyPIpycparser3.0indirect
PyPIpydantic2.13.4indirect
PyPIpydantic-core2.46.4indirect
PyPIpygments2.20.0indirect
PyPIpyjwt2.13.0indirect
PyPIpymdown-extensions11.0.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-multipart0.0.32indirect
PyPIpywin32312indirect
PyPIpyyaml-env-tag1.1indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.34.2indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.16.3indirect
PyPIsix1.17.0indirect
PyPIsniffio1.3.1indirect
PyPIsse-starlette3.4.5indirect
PyPIstarlette1.3.1indirect
PyPItomli2.4.1indirect
PyPItqdm4.68.3indirect
PyPItruststore0.10.4indirect
PyPItypes-jsonschema4.26.0.20260518indirect
PyPItypes-pyyaml6.0.12.20260815indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.2indirect
PyPIuc-micro-py2.0.0indirect
PyPIurllib32.7.0indirect
PyPIuvicorn0.51.0indirect
PyPIwatchdog6.0.0indirect
Dependency advisories 0

Installing pypi:mklang@1.3.5 pulls in 29 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

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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.