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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 12:44 UTC

RDFLib / rdflib

RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.

PythonBSD-3-Clause★ 2.478 Sterne⑂ 598 Forksseit Feb. 2012Auf GitHub ansehen ↗

RDFLib/rdflib erreicht einen Gesundheitsindex von 80 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Engineering Quality (100/100) ab, am schwächsten bei AI Readiness (53/100). Zuletzt vor 3 Tagen aktualisiert. 4 Mitwirkende tragen den Großteil der jüngsten Arbeit.

80
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.

80
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

RDFlibOrganisation
195 Follower39 öffentliche Reposseit Feb. 2012

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIrdflib7.6.0-40vor 155 Tagen

Metriken nach Kategorie

Vitalität

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

73Gut · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 3 Tagen
10.4/36Commit-Rhythmus — 15/52 Wochen mit Commits
16.5/18Commit-Volumen — 68 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 18 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year68
human_commit_share
days_since_last_push3
active_weeks_last_year15
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 22 Releases veröffentlicht
27/36Release-Aktualität — letztes Release vor 155 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 102,9 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count22
latest_release_tag7.6.0
releases_from_tagsnein
days_since_latest_release155
mean_days_between_releases102,9

Community & Verbreitung

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

90Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
55.1/60Stars — 2.478 Stars
23.1/25Forks — 598 Forks
10.5/15Watcher — 77 Watcher
Verwendete Eingangsdaten
forks598
stars2.478
watchers77
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (BSD-3-Clause)
18/18CONTRIBUTING-Leitfaden
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templateja

Nachhaltigkeit & Governance

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

80Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
43.2/54Bus-Faktor — 4 Beitragende decken die Hälfte aller Commits ab
17.5/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 22 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 92 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor4
contributors_sampled100
top_contributor_share0,222
Wie die Bewertung erfolgt
36/46.8Issue-Lösungsquote — 77 % der Issues geschlossen
28.9/38.3PR-Annahme — 1.420/1.881 entschiedene PRs gemergt
6/15OpenSSF Scorecard: Code-Review — Found 8/17 approved changesets -- score normalized to 4
Verwendete Eingangsdaten
merged_prs1.420
open_issues307
closed_issues1.033
issue_closed_ratio0,771
closed_unmerged_prs461
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
16.5/25Reichweite des Inhabers — 195 Follower von RDFLib
23.7/25Kontohistorie — 39 öffentliche Repos, Kontoalter ca. 14 Jahre
Verwendete Eingangsdaten
followers195
owner_typeOrganization
is_verified
owner_loginRDFLib
public_repos39
account_age_days5.279

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 155 Tagen
20/20Versionshistorie — 40 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesrdflib
ecosystemspypi
any_deprecatednein
min_days_since_publish155

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

100Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 3 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration — tox.ini
9.6/9.6Pre-Commit-Hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfigja
has_linter_configja
has_precommit_configja

Dokumentation

100Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://rdflib.readthedocs.org
10/10Repository-Beschreibung
10/10Topics — 20 Topics
10/10Wiki
Verwendete Eingangsdaten
topicsrdflib, semantic-web, linked-data, python, pypi, ntriples, rdf-xml, json-ld, turtle, turtle-rdf, rdf, n3, nquads, serializer, parser, namespace, graph, uri, python-library, sparql
has_wikija
homepagehttps://rdflib.readthedocs.org
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

56Mittel · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0.5/2.5CII-Best-Practices — badge detected: InProgress
3/7.5Code-Review — Found 8/17 approved changesets -- score normalized to 4
2.5/2.5Contributors — project has 92 contributing companies or organizations
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
7.5/7.5Maintained — 18 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
6/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 27 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5,6
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. 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.

53Mittel · 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 — Taskfile.yml, docs/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration — tox.ini
11/11Statische Typprüfung — rdflib/py.typed
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilespoetry.lock
has_dockerfileja
typed_languagenein
bootstrap_filesTaskfile.yml, docs/Makefile
has_devcontainernein
has_linter_configja
typecheck_configsrdflib/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 (rdflib/py.typed)
54.1/55Handhabbare Dateigrößen — 9/537 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes424.141
source_files_sampled537
oversized_source_files9
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — example, examples
Verwendete Eingangsdaten
example_dirsexample, examples
has_mcp_signalnein
api_schema_files

Eckdaten

2.478GitHub-Sterne
100Mitwirkende
68Commits, letzte 12 Monate
3Tage seit letztem Push
22Releases
4Bus-Faktor
307offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 5.6 / 10
5.6Gesamtwert

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 · 2026-07-18 12:43 UTC

10Binary-Artifactsno binaries found in the repo
k. A.Branch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
2CII-Best-Practicesbadge detected: InProgress
4Code-ReviewFound 8/17 approved changesets -- score normalized to 4
10Contributorsproject has 92 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained18 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
8Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities27 existing vulnerabilities detected
Direkte Abhängigkeiten 8
RegistryPaketVersionsvorgabeManifest
PyPIisodate>=0.7.2,<1.0.0pyproject.toml
PyPIpyparsing>=2.1.0,<4pyproject.toml
PyPIberkeleydb^18.1.0pyproject.toml
PyPInetworkx>=2,<4pyproject.toml
PyPIhtml5rdf>=1.2,<2pyproject.toml
PyPIlxml>=4.3,<6.0pyproject.toml
PyPIorjson>=3.9.14,<4pyproject.toml
PyPIhttpx^0.28.1pyproject.toml
Alle Abhängigkeiten 80

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 9 direkte und 71 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIberkeleydb18.1.10direkt
PyPIhtml5rdf1.2.1direkt
PyPIhttpx0.28.1direkt
PyPIisodate0.7.2direkt
PyPIlxml5.4.0direkt
PyPInetworkx3.1direkt
PyPIorjson3.10.15direkt
PyPIpyparsing3.0.9direkt
PyPIpyparsing3.1.4direkt
PyPIanyio4.5.2indirekt
PyPIbabel2.17.0indirekt
PyPIbackrefs5.7.post1indirekt
PyPIblack24.8.0indirekt
PyPIbracex2.6indirekt
PyPIbuild1.2.2.post1indirekt
PyPIcertifi2025.10.5indirekt
PyPIcharset-normalizer3.4.4indirekt
PyPIclick8.1.8indirekt
PyPIcolorama0.4.6indirekt
PyPIcoverage7.6.1indirekt
PyPIdocker7.1.0indirekt
PyPIexceptiongroup1.3.0indirekt
PyPIghp-import2.1.0indirekt
PyPIgriffe1.14.0indirekt
PyPIh110.16.0indirekt
PyPIhttpcore1.0.9indirekt
PyPIidna3.11indirekt
PyPIimportlib-metadata8.5.0indirekt
PyPIiniconfig2.1.0indirekt
PyPIjinja23.1.6indirekt
PyPIlxml-stubs0.5.1indirekt
PyPImarkdown3.7indirekt
PyPImarkupsafe2.1.5indirekt
PyPImergedeep1.3.4indirekt
PyPImkdocs1.6.1indirekt
PyPImkdocs-autorefs1.4.3indirekt
PyPImkdocs-gen-files0.5.0indirekt
PyPImkdocs-get-deps0.2.0indirekt
PyPImkdocs-include-markdown-plugin7.2.0indirekt
PyPImkdocs-material9.7.6indirekt
PyPImkdocs-material-extensions1.3.1indirekt
PyPImkdocstrings0.26.2indirekt
PyPImkdocstrings-python1.13.0indirekt
PyPImypy1.14.1indirekt
PyPImypy-extensions1.1.0indirekt
PyPIpackaging25.0indirekt
PyPIpaginate0.5.7indirekt
PyPIpathspec0.12.1indirekt
PyPIpip25.0.1indirekt
PyPIpip-tools7.5.2indirekt
PyPIplatformdirs4.3.6indirekt
PyPIpluggy1.5.0indirekt
PyPIpoetry1.8.5indirekt
PyPIpygments2.19.2indirekt
PyPIpymdown-extensions10.15indirekt
PyPIpyproject-hooks1.2.0indirekt
PyPIpytest8.3.5indirekt
PyPIpytest-cov5.0.0indirekt
PyPIpython-dateutil2.9.0.post0indirekt
PyPIpython-dotenv1.2.1indirekt
PyPIpytz2025.2indirekt
PyPIpywin32311indirekt
PyPIpyyaml6.0.3indirekt
PyPIpyyaml-env-tag0.1indirekt
PyPIrdflib7.6.0indirekt
PyPIrequests2.32.4indirekt
PyPIruff0.15.0indirekt
PyPIsetuptools71.1.0indirekt
PyPIsix1.17.0indirekt
PyPIsniffio1.3.1indirekt
PyPItestcontainers4.13.3indirekt
PyPItomli2.3.0indirekt
PyPItypes-setuptools71.1.0.20240818indirekt
PyPItyping-extensions4.13.2indirekt
PyPIurllib32.2.3indirekt
PyPIwatchdog4.0.2indirekt
PyPIwcmatch10.1indirekt
PyPIwheel0.45.1indirekt
PyPIwrapt2.0.1indirekt
PyPIzipp3.20.2indirekt
JSON-Rohbericht maschinenlesbar
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      "largest_source_bytes": 424141,
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                "key": "owner_reach",
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                "key": "track_record",
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        ],
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                "key": "fuzzing",
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                "key": "maintained",
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                "key": "sast",
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                "key": "security_policy",
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                "key": "signed_releases",
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              {
                "key": "token_permissions",
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                "points": 6,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "27 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "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"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 8
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "points": 100,
                "status": "met",
                "details": [
                  {
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                    "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",
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        "name": "AI Readiness",
        "value": 53,
        "weight": 0,
        "metrics": [
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            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
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                "params": {
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              },
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                "params": {}
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            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
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                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
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                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
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                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
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            "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"
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              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 87,
            "inputs": {
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              "lockfiles": [
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              ],
              "has_dockerfile": true,
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              "bootstrap_files": [
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                "docs/Makefile"
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              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
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              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
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                "key": "one_command_bootstrap",
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                "points": 18,
                "status": "met",
                "details": [
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                    "code": "file_list",
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                "max_points": 18
              },
              {
                "key": "automated_tests",
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                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
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                "points": 11,
                "status": "met",
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                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
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                "points": 11,
                "status": "met",
                "details": [
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                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Dockerfile, 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 1",
                "points": 1,
                "status": "partial",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 81,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 424141,
              "source_files_sampled": 537,
              "oversized_source_files": 9
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (rdflib/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "rdflib/py.typed",
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                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "9/537 source files over 60KB",
                "points": 54.1,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
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                      "sampled": 537,
                      "oversized": 9
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "example",
                "examples"
              ],
              "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": "example, examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "example, examples"
                    }
                  }
                ],
                "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": [],
  "report_type": "repository",
  "generated_at": "2026-07-18T12:44:23.740677Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/r/RDFLib/rdflib.svg",
  "full_name": "RDFLib/rdflib",
  "license_state": "standard",
  "license_spdx": "BSD-3-Clause"
}

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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 v0.12.0 — vollständige Methodik · Metriken-Wiki.

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