Öffentliches RegisterGut
Software-GesundheitsberichtSchema 0.14.0 · Metriken 1.13.0 · 2026-07-18 23:50 UTC
mitchelllisle / sparkdantic
✨ A Pydantic to PySpark schema library
mitchelllisle/sparkdantic erreicht einen Gesundheitsindex von 73 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (92/100) ab, am schwächsten bei Security (51/100). Zuletzt vor 5 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
73
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
73
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Eigentümerschaft
Mitchell LislePersönliches Konto
20 Follower99 öffentliche Reposseit März 2016
Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | sparkdantic | 2.8.4 | - | 57 | vor 5 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
92
Entwicklungsaktivität
92Exzellent
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 5 Tagen |
| 27.7/36 | Commit-Rhythmus — 40/52 Wochen mit Commits |
| 18/18 | Commit-Volumen — 185 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 21 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 185 |
| human_commit_share | — |
| days_since_last_push | 5 |
| active_weeks_last_year | 40 |
Release-Disziplin
92Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 61 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 5 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 47,5 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 61 |
| latest_release_tag | v2.8.4 |
| releases_from_tags | nein |
| days_since_latest_release | 5 |
| mean_days_between_releases | 47,5 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
58
Popularität & Verbreitung
48Gefährdet
Wie die Bewertung erfolgt
| 34.1/60 | Stars — 128 Stars |
| 10.8/25 | Forks — 21 Forks |
| 3.3/15 | Watcher — 5 Watcher |
Verwendete Eingangsdaten
| forks | 21 |
| stars | 128 |
| watchers | 5 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
70Gut
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (MIT) |
| 18/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | ja |
| has_issue_template | nein |
| has_code_of_conduct | nein |
| has_pull_request_template | nein |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
64
Maintainer-Resilienz (Bus-Faktor)
37Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 8.8/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 61 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 16 Beitragende |
| 6/10 | OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6 |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 16 |
| top_contributor_share | 0,607 |
Wie die Bewertung erfolgt
| 40.3/46.8 | Issue-Lösungsquote — 86 % der Issues geschlossen |
| 36.1/38.3 | PR-Annahme — 805/852 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/4 approved changesets -- score normalized to 0 |
Verwendete Eingangsdaten
| merged_prs | 805 |
| open_issues | 5 |
| closed_issues | 31 |
| issue_closed_ratio | 0,861 |
| closed_unmerged_prs | 47 |
Eigentümerschaft & Trägerschaft
56Mittel
Wie die Bewertung erfolgt
| 10/30 | Organisatorische Trägerschaft — persönliches (Nutzer-)Konto |
| 0/20 | Verifizierte Domain — für Nutzerkonten nicht anwendbar |
| 9.5/25 | Reichweite des Inhabers — 20 Follower von mitchelllisle |
| 25/25 | Kontohistorie — 99 öffentliche Repos, Kontoalter ca. 10 Jahre |
Verwendete Eingangsdaten
| followers | 20 |
| owner_type | User |
| is_verified | — |
| owner_login | mitchelllisle |
| public_repos | 99 |
| account_age_days | 3.764 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 5 Tagen |
| 20/20 | Versionshistorie — 57 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | sparkdantic |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 5 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
92
Engineering-Praktiken
94Exzellent
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 2 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration |
| 9.6/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 16 out of 16 merged PRs checked by a CI test -- score normalized to 10 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | ja |
| has_precommit_config | ja |
Dokumentation
90Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://mitchelllisle.github.io/sparkdantic/ |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 3 Topics |
| 0/10 | Wiki |
Verwendete Eingangsdaten
| topics | pydantic, pyspark, schema |
| has_wiki | nein |
| homepage | https://mitchelllisle.github.io/sparkdantic/ |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
51
Sicherheitslage
51Mittel
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 2.2/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 2.5/2.5 | CI-Tests — 16 out of 16 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/4 approved changesets -- score normalized to 0 |
| 1.5/2.5 | Contributors — project has 2 contributing companies or organizations -- score normalized to 6 |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 7.5/7.5 | Maintained — 21 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — keine Daten |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — keine Daten |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 6/7.5 | Vulnerabilities — 2 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 5,1 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): packaging, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
55
AI-Agentenkontext & Leitlinien
1Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
AI-Verify-Loop (Build / Test / Typprüfung)
86Exzellent
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration |
| 11/11 | Statische Typprüfung — src/sparkdantic/py.typed |
| 10/10 | Reproduzierbare Umgebung — lockfile |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 5/8 | Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | uv.lock |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | src/sparkdantic/py.typed |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
| 27/45 | Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (src/sparkdantic/py.typed) |
| 55/55 | Handhabbare Dateigrößen — 0/23 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 22.575 |
| source_files_sampled | 23 |
| oversized_source_files | 0 |
Eckdaten
128GitHub-Sterne
16Mitwirkende
185Commits, letzte 12 Monate
5Tage seit letztem Push
61Releases
1Bus-Faktor
5offene Issues
PyPIPaket-Ökosysteme
Weitere Details
OpenSSF Scorecard 5.1 / 10
5.1Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 3 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 10 | CI-Tests | 16 out of 16 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/4 approved changesets -- score normalized to 0 |
| 6 | Contributors | project has 2 contributing companies or organizations -- score normalized to 6 |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 21 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| k. A. | Packaging | packaging workflow not detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| k. A. | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 8 | Vulnerabilities | 2 existing vulnerabilities detected |
Direkte Abhängigkeiten 5
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | pydantic | >=2.1.1,<3.0.0 | pyproject.toml |
| PyPI | jmespath | >=1.0.1,<2.0.0 | pyproject.toml |
| PyPI | pyparsing | >=3.1.1,<4.0.0 | pyproject.toml |
| PyPI | packaging | >=24.2,<27.0 | pyproject.toml |
| PyPI | jinja2 | >=3.1.6 | pyproject.toml |
Alle Abhängigkeiten 106
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 5 direkte und 101 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | jinja2 | 3.1.6 | direkt |
| PyPI | jmespath | 1.1.0 | direkt |
| PyPI | packaging | 26.0 | direkt |
| PyPI | pydantic | 2.12.5 | direkt |
| PyPI | pyparsing | 3.3.2 | direkt |
| PyPI | annotated-types | 0.7.0 | indirekt |
| PyPI | attrs | 26.1.0 | indirekt |
| PyPI | babel | 2.18.0 | indirekt |
| PyPI | backports-tarfile | 1.2.0 | indirekt |
| PyPI | backrefs | 6.2 | indirekt |
| PyPI | bump2version | 1.0.1 | indirekt |
| PyPI | bumpversion | 0.6.0 | indirekt |
| PyPI | certifi | 2026.2.25 | indirekt |
| PyPI | cffi | 2.0.0 | indirekt |
| PyPI | cfgv | 3.5.0 | indirekt |
| PyPI | charset-normalizer | 3.4.6 | indirekt |
| PyPI | click | 8.3.1 | indirekt |
| PyPI | colorama | 0.4.6 | indirekt |
| PyPI | coverage | 7.13.5 | indirekt |
| PyPI | cryptography | 48.0.1 | indirekt |
| PyPI | distlib | 0.4.0 | indirekt |
| PyPI | dlint | 0.16.0 | indirekt |
| PyPI | docutils | 0.22.4 | indirekt |
| PyPI | exceptiongroup | 1.3.1 | indirekt |
| PyPI | faker | 37.12.0 | indirekt |
| PyPI | filelock | 3.25.2 | indirekt |
| PyPI | flake8 | 7.3.0 | indirekt |
| PyPI | flake8-bugbear | 24.12.12 | indirekt |
| PyPI | ghp-import | 2.1.0 | indirekt |
| PyPI | griffelib | 2.0.0 | indirekt |
| PyPI | hypothesis | 6.151.9 | indirekt |
| PyPI | id | 1.6.1 | indirekt |
| PyPI | identify | 2.6.18 | indirekt |
| PyPI | idna | 3.15 | indirekt |
| PyPI | importlib-metadata | 9.0.0 | indirekt |
| PyPI | iniconfig | 2.3.0 | indirekt |
| PyPI | jaraco-classes | 3.4.0 | indirekt |
| PyPI | jaraco-context | 6.1.2 | indirekt |
| PyPI | jaraco-functools | 4.4.0 | indirekt |
| PyPI | jeepney | 0.9.0 | indirekt |
| PyPI | keyring | 25.7.0 | indirekt |
| PyPI | librt | 0.8.1 | indirekt |
| PyPI | markdown | 3.10.2 | indirekt |
| PyPI | markdown-it-py | 4.0.0 | indirekt |
| PyPI | markupsafe | 3.0.3 | indirekt |
| PyPI | mccabe | 0.7.0 | indirekt |
| PyPI | mdurl | 0.1.2 | indirekt |
| PyPI | mergedeep | 1.3.4 | indirekt |
| PyPI | mkautodoc | 0.2.0 | indirekt |
| PyPI | mkdocs | 1.6.1 | indirekt |
| PyPI | mkdocs-autorefs | 1.4.4 | indirekt |
| PyPI | mkdocs-gen-files | 0.6.1 | indirekt |
| PyPI | mkdocs-get-deps | 0.2.2 | indirekt |
| PyPI | mkdocs-literate-nav | 0.6.3 | indirekt |
| PyPI | mkdocs-material | 9.7.6 | indirekt |
| PyPI | mkdocs-material-extensions | 1.3.1 | indirekt |
| PyPI | mkdocstrings | 0.30.1 | indirekt |
| PyPI | mkdocstrings-python | 2.0.3 | indirekt |
| PyPI | more-itertools | 10.8.0 | indirekt |
| PyPI | mypy | 1.19.1 | indirekt |
| PyPI | mypy-extensions | 1.1.0 | indirekt |
| PyPI | nh3 | 0.3.3 | indirekt |
| PyPI | nodeenv | 1.10.0 | indirekt |
| PyPI | paginate | 0.5.7 | indirekt |
| PyPI | pathspec | 1.0.4 | indirekt |
| PyPI | pep8-naming | 0.15.1 | indirekt |
| PyPI | platformdirs | 4.9.4 | indirekt |
| PyPI | pluggy | 1.6.0 | indirekt |
| PyPI | pre-commit | 4.5.1 | indirekt |
| PyPI | properdocs | 1.6.7 | indirekt |
| PyPI | py4j | 0.10.9.9 | indirekt |
| PyPI | pycodestyle | 2.14.0 | indirekt |
| PyPI | pycparser | 3.0 | indirekt |
| PyPI | pydantic-core | 2.41.5 | indirekt |
| PyPI | pyflakes | 3.4.0 | indirekt |
| PyPI | pygments | 2.20.0 | indirekt |
| PyPI | pymdown-extensions | 10.21.3 | indirekt |
| PyPI | pyspark | 4.1.1 | indirekt |
| PyPI | pytest | 9.0.3 | indirekt |
| PyPI | pytest-cov | 7.1.0 | indirekt |
| PyPI | pytest-dotenv | 0.5.2 | indirekt |
| PyPI | python-dateutil | 2.9.0.post0 | indirekt |
| PyPI | python-discovery | 1.2.0 | indirekt |
| PyPI | python-dotenv | 1.2.2 | indirekt |
| PyPI | pywin32-ctypes | 0.2.3 | indirekt |
| PyPI | pyyaml | 6.0.3 | indirekt |
| PyPI | pyyaml-env-tag | 1.1 | indirekt |
| PyPI | readme-renderer | 44.0 | indirekt |
| PyPI | requests | 2.33.0 | indirekt |
| PyPI | requests-toolbelt | 1.0.0 | indirekt |
| PyPI | rfc3986 | 2.0.0 | indirekt |
| PyPI | rich | 14.3.3 | indirekt |
| PyPI | secretstorage | 3.5.0 | indirekt |
| PyPI | setuptools | 82.0.1 | indirekt |
| PyPI | six | 1.17.0 | indirekt |
| PyPI | sortedcontainers | 2.4.0 | indirekt |
| PyPI | sparkdantic | 2.8.3 | indirekt |
| PyPI | tomli | 2.4.0 | indirekt |
| PyPI | twine | 6.2.0 | indirekt |
| PyPI | typing-extensions | 4.15.0 | indirekt |
| PyPI | typing-inspection | 0.4.2 | indirekt |
| PyPI | tzdata | 2025.3 | indirekt |
| PyPI | urllib3 | 2.7.0 | indirekt |
| PyPI | virtualenv | 21.2.0 | indirekt |
| PyPI | watchdog | 6.0.0 | indirekt |
| PyPI | zipp | 3.23.0 | indirekt |
JSON-Rohbericht maschinenlesbar
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"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "2 existing vulnerabilities detected",
"points": 6,
"status": "partial",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "excellent",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 7
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "moderate",
"name": "AI Readiness",
"value": 55,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
"has_llms_txt": false,
"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "excellent",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"demonstrated_agent_practice"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 86,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [
"uv.lock"
],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [
"Makefile"
],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [
"src/sparkdantic/py.typed"
],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "Makefile"
}
}
],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 11,
"status": "met",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": "src/sparkdantic/py.typed",
"points": 11,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "src/sparkdantic/py.typed"
}
}
],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": "lockfile",
"points": 10,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "lockfile"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "dependency automation configured, none observed in the sampled commits",
"points": 5,
"status": "partial",
"details": [
{
"code": "dependency_bot_config_only",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "good",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 82,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 22575,
"source_files_sampled": 23,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python with type-check config (src/sparkdantic/py.typed)",
"points": 27,
"status": "partial",
"details": [
{
"code": "typecheck_config_language",
"params": {
"files": "src/sparkdantic/py.typed",
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/23 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 23,
"oversized": 0
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-18T23:50:13.343759Z",
"schema_version": "0.14.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/mitchelllisle/sparkdantic.svg",
"full_name": "mitchelllisle/sparkdantic",
"license_state": "standard",
"license_spdx": "MIT"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.14.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.