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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-16 23:45 UTC

executablebooks / mdit-py-plugins

Collection of core plugins for markdown-it-py

PythonMIT★ 44 Sterne⑂ 37 Forksseit Dez. 2020Auf GitHub ansehen ↗

executablebooks/mdit-py-plugins erreicht einen Gesundheitsindex von 65 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (91/100) ab, am schwächsten bei Security (33/100). Zuletzt heute aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

65
gesamt / 100
Mittel

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.

65
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

Executable BooksOrganisation
523 Follower72 öffentliche Reposseit Nov. 2019

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPImdit-py-plugins0.6.1-22vor 64 Tagenmarkdownmarkdown-itlexerparserdevelopment

Metriken nach Kategorie

Vitalität

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

66Mittel · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
2.8/36Commit-Rhythmus — 4/52 Wochen mit Commits
9.4/18Commit-Volumen — 10 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year10
human_commit_share
days_since_last_push0
active_weeks_last_year4
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 22 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 64 Tagen
12.6/27Release-Rhythmus — ein Release etwa alle 139,4 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count22
latest_release_tagv0.6.1
releases_from_tagsnein
days_since_latest_release64
mean_days_between_releases139,4

Community & Verbreitung

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

63Mittel · 18 % des Gesamtindex
Wie die Bewertung erfolgt
26.5/60Stars — 44 Stars
13/25Forks — 37 Forks
3.9/15Watcher — 6 Watcher
Verwendete Eingangsdaten
forks37
stars44
watchers6
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
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templatenein

Nachhaltigkeit & Governance

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

65Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
6.5/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 71 % der Commits
13.5/13.5Breite der Beitragenden — 17 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor1
contributors_sampled17
top_contributor_share0,71
Wie die Bewertung erfolgt
24.6/46.8Issue-Lösungsquote — 53 % der Issues geschlossen
33.1/38.3PR-Annahme — 83/96 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs83
open_issues18
closed_issues20
issue_closed_ratio0,526
closed_unmerged_prs13
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
19.6/25Reichweite des Inhabers — 523 Follower von executablebooks
25/25Kontohistorie — 72 öffentliche Repos, Kontoalter ca. 6 Jahre
Verwendete Eingangsdaten
followers523
owner_typeOrganization
is_verified
owner_loginexecutablebooks
public_repos72
account_age_days2.438

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 64 Tagen
20/20Versionshistorie — 22 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesmdit-py-plugins
ecosystemspypi
any_deprecatednein
min_days_since_publish64

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

91Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 2 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — tox.ini
9.6/9.6Pre-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_configja

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://mdit-py-plugins.readthedocs.io
10/10Repository-Beschreibung
10/10Topics — 3 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsmarkdown-it, plugin, markdown
has_wikinein
homepagehttps://mdit-py-plugins.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
manifestspyproject.toml
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.

70Gut · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesAGENTS.md
agent_instruction_max_bytes11.892
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — tox.ini
11/11Statische Typprüfung — mdit_py_plugins/py.typed
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_files
has_devcontainernein
has_linter_configja
typecheck_configsmdit_py_plugins/py.typed
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 (mdit_py_plugins/py.typed)
55/55Handhabbare Dateigrößen — 0/60 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes14.623
source_files_sampled60
oversized_source_files0

Eckdaten

44GitHub-Sterne
17Mitwirkende
10Commits, letzte 12 Monate
0Tage seit letztem Push
22Releases
1Bus-Faktor
18offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • OpenSSF Scorecard did not return a usable result (Skipping github.com/executablebooks/mdit-py-plugins: run: repo unreachable: GET https://api.github.com/repos/executablebooks/mdit-py-plugins: 503 []); skipping Scorecard checks

Weitere Details

Direkte Abhängigkeiten 1
RegistryPaketVersionsvorgabeManifest
PyPImarkdown-it-py>=2.0.0,<5.0.0pyproject.toml
Alle Abhängigkeiten 2

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 1 direkte und 1 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPImarkdown-it-pydirekt
PyPIflit-coreindirekt
JSON-Rohbericht maschinenlesbar
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      "is_fork": false,
      "size_kb": 296,
      "has_wiki": false,
      "homepage": "https://mdit-py-plugins.readthedocs.io",
      "languages": {
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      "pushed_at": "2026-07-16T14:09:26Z",
      "created_at": "2020-12-14T16:41:37Z",
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            "Programming Language :: Python :: 3.11",
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            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3.9",
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            "Programming Language :: Python :: Implementation :: PyPy",
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      "api_schema_files": [],
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      "typecheck_configs": [
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      "largest_source_bytes": 14623,
      "source_files_sampled": 60,
      "oversized_source_files": 0,
      "agent_instruction_files": [
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      "agent_instruction_max_bytes": 11892
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    "dependencies": {
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      ],
      "ecosystems": [
        "pypi"
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      "dependencies": [
        {
          "name": "markdown-it-py",
          "manifest": "pyproject.toml",
          "ecosystem": "pypi",
          "version_constraint": ">=2.0.0,<5.0.0"
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      "all_dependencies": {
        "error": null,
        "source": "github-sbom",
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      "linter_configs": [
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      "has_linter_config": true,
      "has_precommit_config": true
    },
    "security_signals": {
      "lockfiles": [],
      "scorecard": null,
      "has_codeql_workflow": false,
      "has_security_policy": false,
      "has_dependabot_config": true
    }
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    "disabled_metrics": [],
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  "metrics": {
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      "inputs": {
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        "community": 63,
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      },
      "components": []
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    "categories": [
      {
        "key": "vitality",
        "band": "moderate",
        "name": "Vitality",
        "value": 66,
        "weight": 0.22,
        "metrics": [
          {
            "key": "development_activity",
            "band": "moderate",
            "name": "Development activity",
            "note": null,
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            "inputs": {
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              "days_since_last_push": 0,
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            },
            "components": [
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              },
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                "key": "commit_cadence",
                "name": "Commit cadence",
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                "key": "commit_volume",
                "name": "Commit volume",
                "detail": "10 commits in the last year",
                "points": 9.4,
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                ],
                "max_points": 18
              },
              {
                "key": "openssf_scorecard_maintained",
                "name": "OpenSSF Scorecard: Maintained",
                "detail": "OpenSSF Scorecard unavailable",
                "points": 0,
                "status": "excluded",
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                "max_points": 10
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          },
          {
            "key": "release_discipline",
            "band": "good",
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            "note": null,
            "notes": [],
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            "inputs": {
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            },
            "components": [
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                "key": "ships_releases",
                "name": "Ships releases",
                "detail": "22 releases published",
                "points": 27,
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                "max_points": 36
              },
              {
                "key": "release_cadence",
                "name": "Release cadence",
                "detail": "a release every ~139.4 days",
                "points": 12.6,
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                "key": "linter_config",
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                "key": "openssf_scorecard_ci_tests",
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                "key": "documentation_homepage_site",
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                "max_points": 10
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                "key": "wiki",
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                "status": "missed",
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        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
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        "name": "Security",
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        "weight": 0.16,
        "metrics": [
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            "key": "security_posture",
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            "name": "Security posture",
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              {
                "code": "weights_renormalized",
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            "value": 33,
            "inputs": {
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            "components": [
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                "key": "security_policy_security_md",
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                "points": 0,
                "status": "missed",
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              {
                "key": "dependabot_config",
                "name": "Dependabot config",
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                "points": 25,
                "status": "met",
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                "key": "dependency_lockfiles",
                "name": "Dependency lockfiles",
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                "points": 0,
                "status": "excluded",
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                "max_points": 25
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              {
                "key": "codeql_workflow",
                "name": "CodeQL workflow",
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                "points": 0,
                "status": "missed",
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          },
          {
            "key": "high_risk_jurisdiction_exposure",
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            "notes": [
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            "value": 100,
            "inputs": {
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              "review_only_matches": 0,
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            "components": [
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                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "status": "met",
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        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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        "name": "AI Readiness",
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        "weight": 0,
        "metrics": [
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              "agent_instruction_max_bytes": 11892
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                "status": "met",
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                "max_points": 45
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                "key": "machine_readable_docs_llms_txt",
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          },
          {
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            "components": [
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              {
                "key": "automated_tests",
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              {
                "key": "lint_format_config",
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                "status": "met",
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                "max_points": 11
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              {
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                "status": "met",
                "details": [
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                      "files": "mdit_py_plugins/py.typed"
                    }
                  }
                ],
                "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",
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                  {
                    "code": "dependency_bot_config_only",
                    "params": {}
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                ],
                "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
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          {
            "key": "ai_code_legibility",
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            "name": "Code legibility for models",
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            "notes": [],
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                "details": [
                  {
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                    "params": {
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                      "language": "Python"
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/60 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
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                ],
                "max_points": 55
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            ]
          }
        ],
        "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"
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  "warnings": [
    "OpenSSF Scorecard did not return a usable result (Skipping github.com/executablebooks/mdit-py-plugins: run: repo unreachable: GET https://api.github.com/repos/executablebooks/mdit-py-plugins: 503  []); skipping Scorecard checks"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-16T23:45:47.032497Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/e/executablebooks/mdit-py-plugins.svg",
  "full_name": "executablebooks/mdit-py-plugins",
  "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 v0.11.0 — vollständige Methodik · Metriken-Wiki.

Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte StatistikenPyPI.