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Software-GesundheitsberichtSchema 0.16.0 · Metriken 1.13.0 · 2026-07-21 02:29 UTC

thombashi / DataProperty

A Python library for extract property from data.

PythonMIT★ 17 Sterne⑂ 5 Forksseit Feb. 2016Auf GitHub ansehen ↗

thombashi/DataProperty erreicht einen Gesundheitsindex von 55 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (72/100) ab, am schwächsten bei Community & Adoption (36/100). Zuletzt vor 29 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

55
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.

55
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

Tsuyoshi HombashiPersönliches Konto
131 Follower99 öffentliche Reposseit Okt. 2015

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

Metriken nach Kategorie

Vitalität

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

62Mittel · 22 % des Gesamtindex
Wie die Bewertung erfolgt
28.8/36Push-Aktualität — letzter Push vor 29 Tagen
1.4/36Commit-Rhythmus — 2/52 Wochen mit Commits
9.4/18Commit-Volumen — 10 Commits im letzten Jahr
7/10OpenSSF Scorecard: Maintained — 9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
Verwendete Eingangsdaten
commits_last_year10
human_commit_share
days_since_last_push29
active_weeks_last_year2
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 47 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 72 Tagen
12.6/27Release-Rhythmus — ein Release etwa alle 195,1 Tage
8/10OpenSSF Scorecard: Signed-Releases — 3 out of the last 3 releases have a total of 3 signed artifacts.
Verwendete Eingangsdaten
releases_count47
latest_release_tagv1.1.1
releases_from_tagsnein
days_since_latest_release72
mean_days_between_releases195,1

Community & Verbreitung

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

36Gefährdet · 18 % des Gesamtindex
Wie die Bewertung erfolgt
19.5/60Stars — 17 Stars
5/25Forks — 5 Forks
0/15Watcher — 1 Watcher
Verwendete Eingangsdaten
forks5
stars17
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein

Nachhaltigkeit & Governance

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

45Gefährdet · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
0.1/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 100 % der Commits
5.4/13.5Breite der Beitragenden — 4 Beitragende
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Verwendete Eingangsdaten
bus_factor1
contributors_sampled4
top_contributor_share0,997
Wie die Bewertung erfolgt
31.2/46.8Issue-Lösungsquote — 67 % der Issues geschlossen
33/38.3PR-Annahme — 56/65 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — Found 0/24 approved changesets -- score normalized to 0
Verwendete Eingangsdaten
merged_prs56
open_issues1
closed_issues2
issue_closed_ratio0,667
closed_unmerged_prs9
Wie die Bewertung erfolgt
10/30Organisatorische Trägerschaft — persönliches (Nutzer-)Konto
0/20Verifizierte Domain — für Nutzerkonten nicht anwendbar
15.2/25Reichweite des Inhabers — 131 Follower von thombashi
25/25Kontohistorie — 99 öffentliche Repos, Kontoalter ca. 10 Jahre
Verwendete Eingangsdaten
followers131
owner_typeUser
is_verified
owner_loginthombashi
public_repos99
account_age_days3.915
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

72Gut · 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
12/20OpenSSF Scorecard: CI-Tests — 2 out of 3 merged PRs checked by a CI test -- score normalized to 6
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_confignein
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://pypi.python.org/pypi/DataProperty
10/10Repository-Beschreibung
10/10Topics — 4 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsdata, python-library, property, python
has_wikinein
homepagehttps://pypi.python.org/pypi/DataProperty
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

62Mittel · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
1.5/2.5CI-Tests — 2 out of 3 merged PRs checked by a CI test -- score normalized to 6
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/24 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Lizenz — license file detected
5.2/7.5Maintained — 9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
6/7.5Signed-Releases — 3 out of the last 3 releases have a total of 3 signed artifacts.
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate6,2

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.

48Gefährdet · 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
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — tox.ini
11/11Statische Typprüfung — dataproperty/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 — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile
has_devcontainernein
has_linter_configja
typecheck_configsdataproperty/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 (dataproperty/py.typed)
55/55Handhabbare Dateigrößen — 0/36 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes31.696
source_files_sampled36
oversized_source_files0
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples, notebooks
Verwendete Eingangsdaten
example_dirsexamples, notebooks
has_mcp_signalnein
api_schema_files

Eckdaten

17GitHub-Sterne
4Mitwirkende
10Commits, letzte 12 Monate
29Tage seit letztem Push
47Releases
1Bus-Faktor
1offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • No resolved dependencies carried a version and a supported ecosystem

Weitere Details

OpenSSF Scorecard 6.2 / 10
6.2Gesamtwert

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).Scorecard v5.5.0 · 2026-07-21 02:29 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
6CI-Tests2 out of 3 merged PRs checked by a CI test -- score normalized to 6
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/24 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
7Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
8Signed-Releases3 out of the last 3 releases have a total of 3 signed artifacts.
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Alle Abhängigkeiten 7

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 7 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPImbstrdecoderindirekt
PyPIpytestindirekt
PyPIpytest-md-reportindirekt
PyPIsphinxindirekt
PyPIsphinx-rtd-themeindirekt
PyPItcolorpyindirekt
PyPItypepyindirekt
Abhängigkeits-Advisories nicht bewertet

Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies carried a version and a supported ecosystem

JSON-Rohbericht maschinenlesbar
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              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7",
                "points": 5.2,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is run on all commits",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "3 out of the last 3 releases have a total of 3 signed artifacts.",
                "points": 6,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "GitHub workflow tokens follow principle of least privilege",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "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": 10
            },
            "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": "at_risk",
        "name": "AI Readiness",
        "value": 48,
        "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": 74,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "dataproperty/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": "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": "dataproperty/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "dataproperty/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",
                "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": 31696,
              "source_files_sampled": 36,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (dataproperty/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "dataproperty/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/36 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 36,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples",
                "notebooks"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples, notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples, notebooks"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "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": [
    "No resolved dependencies carried a version and a supported ecosystem"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-21T02:29:47.901882Z",
  "schema_version": "0.16.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/t/thombashi/DataProperty.svg",
  "full_name": "thombashi/DataProperty",
  "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 v0.16.0 — vollständige Methodik · Metriken-Wiki.

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