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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-17 00:26 UTC

joke2k / faker

Faker is a Python package that generates fake data for you.

PythonMIT★ 19.336 Sterne⑂ 2.101 Forksseit Nov. 2012Auf GitHub ansehen ↗

joke2k/faker erreicht einen Gesundheitsindex von 76 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Community & Adoption (92/100) ab, am schwächsten bei Security (33/100). Zuletzt vor 2 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

76
gesamt / 100
Gut

Software-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.

76
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)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

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

Daniele FaragliaPersönliches Konto
563 Follower41 öffentliche Reposseit Aug. 2010Self Employed

Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPIfaker40.31.0-496vor 2 Tagenfakerfixturesdatatestmockgenerator

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

89Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 2 Tagen
20.1/36Commit-Rhythmus — 29/52 Wochen mit Commits
18/18Commit-Volumen — 270 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year270
human_commit_share
days_since_last_push2
active_weeks_last_year29

Release-Disziplin

100Exzellent
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 2 Tagen
27/27Release-Rhythmus — ein Release etwa alle 1,6 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count100
latest_release_tagv40.31.0
releases_from_tagsnein
days_since_latest_release2
mean_days_between_releases1,6

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

92Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 19.336 Stars
25/25Forks — 2.101 Forks
13/15Watcher — 218 Watcher
Verwendete Eingangsdaten
forks2.101
stars19.336
watchers218
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
18/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
7.2/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templateja
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

70Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
7.5/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 66 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor1
contributors_sampled100
top_contributor_share0,665
Wie die Bewertung erfolgt
46.4/46.8Issue-Lösungsquote — 99 % der Issues geschlossen
32/38.3PR-Annahme — 1.299/1.553 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs1.299
open_issues7
closed_issues831
issue_closed_ratio0,992
closed_unmerged_prs254
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
19.8/25Reichweite des Inhabers — 563 Follower von joke2k
23.8/25Kontohistorie — 41 öffentliche Repos, Kontoalter ca. 15 Jahre
Verwendete Eingangsdaten
followers563
owner_typeUser
is_verified
owner_loginjoke2k
public_repos41
account_age_days5.820
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 2 Tagen
20/20Versionshistorie — 496 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesfaker
ecosystemspypi
any_deprecatednein
min_days_since_publish2

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

88Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 3 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — tox.ini
0/9.6Pre-Commit-Hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — keine Daten
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_confignein

Dokumentation

100Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://faker.readthedocs.io
10/10Repository-Beschreibung
10/10Topics — 9 Topics
10/10Wiki
Verwendete Eingangsdaten
topicspython, fake, testing, dataset, fake-data, test-data, test-data-generator, faker, faker-generator
has_wikija
homepagehttps://faker.readthedocs.io
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

33Gefährdet · 16 % des Gesamtindex

Sicherheitslage

33Gefährdet
Wie die Bewertung erfolgt
0/30Sicherheitsrichtlinie (SECURITY.md)
25/25Dependabot-Konfiguration
0/25Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet
0/20CodeQL-Workflow
Verwendete Eingangsdaten
sourcefile_signals
lockfiles
manifestssetup.cfg, setup.py
has_codeql_workflownein
has_security_policynein
has_dependabot_configja
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. 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.

54Mittel · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
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.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — Makefile, docs/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — tox.ini
11/11Statische Typprüfung — faker/py.typed, mypy.ini
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
0/10OpenSSF Scorecard: Pinned-Dependencies — keine Daten
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile, docs/Makefile
has_devcontainernein
has_linter_configja
typecheck_configsfaker/py.typed, mypy.ini
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (faker/py.typed, mypy.ini)
53/55Handhabbare Dateigrößen — 30/813 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes769.957
source_files_sampled813
oversized_source_files30

Eckdaten

19.336GitHub-Sterne
100Mitwirkende
270Commits, letzte 12 Monate
2Tage seit letztem Push
100Releases
1Bus-Faktor
7offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

Weitere Details

Alle Abhängigkeiten 24

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 24 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIblackindirekt
PyPIcheck-manifestindirekt
PyPIcoverageindirekt
PyPIdoc8indirekt
PyPIemail-validator1.0.3indirekt
PyPIflake8indirekt
PyPIflake8-comprehensionsindirekt
PyPIfreezegunindirekt
PyPIisortindirekt
PyPImock2.0.0indirekt
PyPImypyindirekt
PyPImypy-extensionsindirekt
PyPIpackagingindirekt
PyPIpytestindirekt
PyPIpython-dateutilindirekt
PyPIsetuptoolsindirekt
PyPIsixindirekt
PyPItext-unidecode1.2indirekt
PyPItoxindirekt
PyPItwineindirekt
PyPItzdataindirekt
PyPIukpostcodeparser1.1.2indirekt
PyPIvalidatorsindirekt
PyPIwheelindirekt
JSON-Rohbericht maschinenlesbar
{
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    "repo": {
      "topics": [
        "python",
        "fake",
        "testing",
        "dataset",
        "fake-data",
        "test-data",
        "test-data-generator",
        "faker",
        "faker-generator"
      ],
      "is_fork": false,
      "size_kb": 11974,
      "has_wiki": true,
      "homepage": "https://faker.readthedocs.io",
      "languages": {
        "Shell": 387,
        "Python": 9775259,
        "Makefile": 410
      },
      "pushed_at": "2026-07-14T15:33:27Z",
      "created_at": "2012-11-12T23:00:09Z",
      "owner_type": "User",
      "updated_at": "2026-07-16T20:07:22Z",
      "description": "Faker is a Python package that generates fake data for you.",
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      "is_disabled": false,
      "license_spdx": "MIT",
      "default_branch": "master",
      "primary_language": "Python",
      "significant_languages": [
        "Python"
      ]
    },
    "owner": {
      "blog": "http://daniele.faraglia.info",
      "name": "Daniele Faraglia",
      "type": "User",
      "login": "joke2k",
      "company": "Self Employed",
      "location": "Brighton, UK",
      "followers": 563,
      "avatar_url": "https://avatars.githubusercontent.com/u/359076?v=4",
      "created_at": "2010-08-09T20:47:11Z",
      "is_verified": null,
      "public_repos": 41,
      "account_age_days": 5820
    },
    "activity": {
      "releases_count": 100,
      "commits_last_year": 270,
      "latest_release_at": "2026-07-14T15:33:15Z",
      "latest_release_tag": "v40.31.0",
      "releases_from_tags": false,
      "days_since_last_push": 2,
      "active_weeks_last_year": 29,
      "days_since_latest_release": 2,
      "mean_days_between_releases": 1.6
    },
    "community": {
      "has_readme": true,
      "has_license": true,
      "has_description": true,
      "has_contributing": true,
      "health_percentage": 71,
      "has_issue_template": true,
      "has_code_of_conduct": false,
      "has_pull_request_template": true
    },
    "ecosystem": {
      "packages": [
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          "name": "faker",
          "exists": true,
          "license": "MIT License",
          "keywords": [
            "faker",
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            "data",
            "test",
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            "Development Status :: 5 - Production/Stable",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.10",
            "Programming Language :: Python :: 3.11",
            "Programming Language :: Python :: 3.12",
            "Programming Language :: Python :: 3.13",
            "Programming Language :: Python :: 3.14",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: Software Development :: Testing",
            "Topic :: Utilities"
          ],
          "ecosystem": "pypi",
          "matches_repo": true,
          "registry_url": "https://pypi.org/project/faker/",
          "is_deprecated": false,
          "latest_version": "40.31.0",
          "repository_url": "https://github.com/joke2k/faker",
          "versions_count": 496,
          "total_downloads": null,
          "dependents_count": null,
          "deprecation_note": null,
          "maintainers_count": null,
          "monthly_downloads": null,
          "first_published_at": "2010-12-23T20:57:59.156828Z",
          "latest_published_at": "2026-07-14T15:33:32.045535Z",
          "latest_version_yanked": null,
          "days_since_latest_publish": 2
        }
      ]
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    "popularity": {
      "forks": 2101,
      "stars": 19336,
      "watchers": 218,
      "open_issues_and_prs": 32
    },
    "ai_readiness": {
      "has_nix": false,
      "example_dirs": [],
      "has_llms_txt": false,
      "has_dockerfile": false,
      "has_mcp_signal": false,
      "bootstrap_files": [
        "Makefile",
        "docs/Makefile"
      ],
      "api_schema_files": [],
      "has_devcontainer": false,
      "typecheck_configs": [
        "faker/py.typed",
        "mypy.ini"
      ],
      "largest_source_bytes": 769957,
      "source_files_sampled": 813,
      "oversized_source_files": 30,
      "agent_instruction_files": [],
      "agent_instruction_max_bytes": null
    },
    "dependencies": {
      "manifests": [
        "setup.cfg",
        "setup.py"
      ],
      "ecosystems": [
        "pypi"
      ],
      "dependencies": [],
      "all_dependencies": {
        "error": null,
        "source": "github-sbom",
        "packages": [
          {
            "name": "black",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "check-manifest",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "coverage",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "doc8",
            "direct": false,
            "version": null,
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          {
            "name": "email-validator",
            "direct": false,
            "version": "1.0.3",
            "ecosystem": "pypi"
          },
          {
            "name": "flake8",
            "direct": false,
            "version": null,
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          },
          {
            "name": "flake8-comprehensions",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "freezegun",
            "direct": false,
            "version": null,
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          {
            "name": "isort",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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          {
            "name": "mock",
            "direct": false,
            "version": "2.0.0",
            "ecosystem": "pypi"
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          {
            "name": "mypy",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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            "name": "mypy-extensions",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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          {
            "name": "packaging",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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            "name": "pytest",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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            "name": "python-dateutil",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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            "name": "setuptools",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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            "name": "six",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
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          {
            "name": "text-unidecode",
            "direct": false,
            "version": "1.2",
            "ecosystem": "pypi"
          },
          {
            "name": "tox",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "twine",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "tzdata",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "ukpostcodeparser",
            "direct": false,
            "version": "1.1.2",
            "ecosystem": "pypi"
          },
          {
            "name": "validators",
            "direct": false,
            "version": null,
            "ecosystem": "pypi"
          },
          {
            "name": "wheel",
            "direct": false,
            "version": null,
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        "collected": true,
        "truncated": false,
        "total_count": 24,
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        "indirect_count": 24
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        "merged_prs": 1299,
        "open_issues": 7,
        "closed_ratio": 0.992,
        "closed_issues": 831,
        "closed_unmerged_prs": 254
      },
      "bus_factor": 1,
      "top_contributors": [
        {
          "type": "User",
          "login": "fcurella",
          "commits": 2270,
          "avatar_url": "https://avatars.githubusercontent.com/u/89607?u=80827cda3413f129e99a83c4c9c1f6e308a5e998&v=4"
        },
        {
          "type": "User",
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          "commits": 198,
          "avatar_url": "https://avatars.githubusercontent.com/u/359076?u=f6f0bce5d0882c44a01c4bf5e328f69877cca4a1&v=4"
        },
        {
          "type": "User",
          "login": "jremes-foss",
          "commits": 85,
          "avatar_url": "https://avatars.githubusercontent.com/u/4118513?u=8735927242441e87b784c2bd59c5eaa51c9bb3ca&v=4"
        },
        {
          "type": "User",
          "login": "mdxs",
          "commits": 52,
          "avatar_url": "https://avatars.githubusercontent.com/u/1143642?v=4"
        },
        {
          "type": "User",
          "login": "illia-v",
          "commits": 38,
          "avatar_url": "https://avatars.githubusercontent.com/u/17710133?u=86e279bcb4f15d8a29e8d5679a56285c4b70ae50&v=4"
        },
        {
          "type": "User",
          "login": "reverbc",
          "commits": 36,
          "avatar_url": "https://avatars.githubusercontent.com/u/783515?u=c3c872db2fdbdab402610c80a736bda7b9c2c96e&v=4"
        },
        {
          "type": "User",
          "login": "malefice",
          "commits": 29,
          "avatar_url": "https://avatars.githubusercontent.com/u/7114869?v=4"
        },
        {
          "type": "User",
          "login": "george0st",
          "commits": 28,
          "avatar_url": "https://avatars.githubusercontent.com/u/95856749?u=fb596e6dea41aea7a097da73f8fb63e4fad5cdc7&v=4"
        },
        {
          "type": "User",
          "login": "jdufresne",
          "commits": 26,
          "avatar_url": "https://avatars.githubusercontent.com/u/347634?u=6506c89dcbfdfd43c26ce41c972cacfc20cff5ef&v=4"
        },
        {
          "type": "User",
          "login": "grantbachman",
          "commits": 24,
          "avatar_url": "https://avatars.githubusercontent.com/u/499564?u=9aacb4c2ce61bb400dc5353bbd3323741d95e402&v=4"
        }
      ],
      "contributors_sampled": 100,
      "top_contributor_share": 0.665
    },
    "quality_signals": {
      "has_ci": true,
      "has_tests": true,
      "ci_workflows": [
        "ci.yml",
        "gh-release.yml",
        "issues.yml"
      ],
      "has_docs_dir": true,
      "linter_configs": [
        "tox.ini"
      ],
      "has_editorconfig": false,
      "has_linter_config": true,
      "has_precommit_config": false
    },
    "security_signals": {
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                "key": "dependabot_config",
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                "key": "dependency_lockfiles",
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                "points": 0,
                "status": "excluded",
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                "key": "codeql_workflow",
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          },
          {
            "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": 8
            },
            "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": 54,
        "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": "good",
            "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": 84,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "Makefile",
                "docs/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "faker/py.typed",
                "mypy.ini"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "Makefile, docs/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Makefile, docs/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": "tox.ini",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "tox.ini"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "faker/py.typed, mypy.ini",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "faker/py.typed, mypy.ini"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "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": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 80,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 769957,
              "source_files_sampled": 813,
              "oversized_source_files": 30
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (faker/py.typed, mypy.ini)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "faker/py.typed, mypy.ini",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "30/813 source files over 60KB",
                "points": 53,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 813,
                      "oversized": 30
                    }
                  }
                ],
                "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": [
    "OpenSSF Scorecard timed out after 240s; skipping Scorecard checks"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-17T00:26:07.884193Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/j/joke2k/faker.svg",
  "full_name": "joke2k/faker",
  "license_state": "standard",
  "license_spdx": "MIT"
}

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Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.11.0 — vollständige Methodik · Metriken-Wiki.

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