Registro público
Informe de salud del softwareesquema 0.12.0 · métricas 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★ 2478 estrellas⑂ 598 forksdesde feb 2012Ver en GitHub ↗

RDFLib/rdflib tiene un índice de salud de 80 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Engineering Quality (100/100) y la más baja, AI Readiness (53/100). Se actualizó por última vez hace 3 días. 4 personas concentran la mayor parte del trabajo reciente.

80
global / 100
Bueno

Índice de salud del software

Las métricas se agrupan en categorías ponderadas sobre una escala de 1 a 100. El resultado global parte de su media; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe el límite 49 (En riesgo). Preparación para IA queda fuera.

80
Excelente85-100Ejemplar; cumple prácticamente todos los criterios evaluados
Bueno70-84Saludable; carencias menores
Moderado50-69Aceptable con carencias notables; se recomienda revisión
En riesgo30-49Debilidades significativas; su adopción exige cautela
Crítico1-29Problemas graves (proyecto abandonado, un solo mantenedor, sin higiene)
VitalidadComunidad yAdopciónSostenibilidady GobernanzaCalidad deIngenieríaSeguridadPreparaciónpara IA

Perfil de puntuación

Cada eje es una categoría. La forma importa más que la media: un proyecto sano llena toda la figura, mientras que un perfil de picos y cráteres indica que la fortaleza en una dimensión enmascara el riesgo en otra.

Titularidad

RDFlibOrganización
195 seguidores39 repositorios públicosdesde feb 2012

Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.

Ecosistemas de paquetes

RegistroPaqueteVersiónDescargas / mesVersionesÚltima publicación
PyPIrdflib7.6.0-40hace 155 días

Métricas por categoría

Vitalidad

¿Está vivo el proyecto: se escribe código y se publican versiones?

73Bueno · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 3 días
10.4/36Cadencia de commits — 15/52 semanas con commits
16.5/18Volumen de commits — 68 commits en el último año
10/10OpenSSF Scorecard: Maintained — 18 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year68
human_commit_share
days_since_last_push3
active_weeks_last_year15
Cómo se puntúa
27/27Publica versiones — 22 versiones publicadas
27/36Recencia de las versiones — última versión hace 155 días
19.8/27Cadencia de publicación — una versión cada ~102,9 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count22
latest_release_tag7.6.0
releases_from_tagsno
days_since_latest_release155
mean_days_between_releases102,9

Comunidad y Adopción

¿Tiene el proyecto usuarios, descargas, atención y unas condiciones acogedoras para quienes contribuyen?

90Excelente · 18% del índice global
Cómo se puntúa
55.1/60Estrellas — 2478 estrellas
23.1/25Forks — 598 forks
10.5/15Observadores — 77 observadores
Datos de entrada utilizados
forks598
stars2478
watchers77
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (BSD-3-Clause)
18/18Guía CONTRIBUTING
13.5/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_templateno
has_code_of_conduct
has_pull_request_template

Sostenibilidad y Gobernanza

¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?

80Bueno · 24% del índice global
Cómo se puntúa
43.2/54Factor bus — la mitad de los commits recae en 4 contribuyente(s)
17.5/22.5Distribución de commits — el principal contribuyente firma el 22% de los commits
13.5/13.5Amplitud de contribuyentes — 100 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 92 contributing companies or organizations
Datos de entrada utilizados
bus_factor4
contributors_sampled100
top_contributor_share0,222
Cómo se puntúa
36/46.8Resolución de issues — 77% de issues cerradas
28.9/38.3Aceptación de PR — 1420/1881 PR decididos fusionados
6/15OpenSSF Scorecard: Code-Review — Found 8/17 approved changesets -- score normalized to 4
Datos de entrada utilizados
merged_prs1420
open_issues307
closed_issues1033
issue_closed_ratio0,771
closed_unmerged_prs461
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
16.5/25Alcance del propietario — 195 seguidores de RDFLib
23.7/25Trayectoria — 39 repos públicos, cuenta de ~14 años
Datos de entrada utilizados
followers195
owner_typeOrganization
is_verified
owner_loginRDFLib
public_repos39
account_age_days5279
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 155 días
20/20Historial de versiones — 40 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesrdflib
ecosystemspypi
any_deprecatedno
min_days_since_publish155

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

100Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 3 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — tox.ini
9.6/9.6Hooks de pre-commit
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
Datos de entrada utilizados
has_ci
has_tests
has_editorconfig
has_linter_config
has_precommit_config

Documentación

100Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://rdflib.readthedocs.org
10/10Descripción del repositorio
10/10Topics — 20 topics
10/10Wiki
Datos de entrada utilizados
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_wiki
homepagehttps://rdflib.readthedocs.org
has_readme
has_docs_dir
has_description

Seguridad

¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?

56Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
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
2.5/2.5Licencia — 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
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5,6
Excluidos de la puntuación (sin datos o no aplicable): branch_protection. Los pesos restantes se han renormalizado.

Preparación para IA

¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Es una insignia independiente y experimental — peso 0,0, de modo que se presenta por separado y no afecta a la puntuación de salud global.

53Moderado · 0% del índice global
Cómo se puntúa
0/45Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor
0/15Documentación legible por máquinas (llms.txt)
0/40Historial de commits legible — sin datos
Datos de entrada utilizados
has_llms_txtno
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
18/18Arranque con un solo comando — Taskfile.yml, docs/Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — tox.ini
11/11Verificación estática de tipos — rdflib/py.typed
10/10Entorno reproducible — Dockerfile, lockfile
0/10Práctica demostrada con agentes — sin datos
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Datos de entrada utilizados
has_nixno
has_tests
lockfilespoetry.lock
has_dockerfile
typed_languageno
bootstrap_filesTaskfile.yml, docs/Makefile
has_devcontainerno
has_linter_config
typecheck_configsrdflib/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes. Los pesos restantes se han renormalizado.
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (rdflib/py.typed)
54.1/55Tamaños de archivo manejables — 9/537 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes424.141
source_files_sampled537
oversized_source_files9
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — example, examples
Datos de entrada utilizados
example_dirsexample, examples
has_mcp_signalno
api_schema_files

Datos clave

2478estrellas de GitHub
100contribuidores
68commits en los últimos 12 meses
3días desde el último push
22versiones publicadas
4factor bus
307issues abiertas
PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 5.6 / 10
5.6agregado

Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-07-18 12:43 UTC

10Binary-Artifactsno binaries found in the repo
n/dBranch-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
Dependencias directas 8
RegistroPaqueteRestricción de versiónManifiesto
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
Todas las dependencias 80

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 9 paquetes directos y 71 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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PyPInetworkx3.1directa
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Informe JSON sin procesar legible por máquina
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                "key": "pr_acceptance",
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                "key": "owner_reach",
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              {
                "key": "track_record",
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                    "code": "account_age_years",
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            "key": "package_maintenance",
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        ],
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                "key": "fuzzing",
                "name": "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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                "key": "vulnerabilities",
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            ]
          },
          {
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            "notes": [
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                "code": "jurisdiction_evidence_limits",
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            ],
            "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",
                "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": 53,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "excellent",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 87,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
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              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
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                "docs/Makefile"
              ],
              "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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                "details": [
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                "max_points": 18
              },
              {
                "key": "automated_tests",
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                "points": 22,
                "status": "met",
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              },
              {
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                "points": 11,
                "status": "met",
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                ],
                "max_points": 11
              },
              {
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                "points": 11,
                "status": "met",
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                ],
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              },
              {
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                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
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                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
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                    "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",
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                  }
                ],
                "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": {
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              "largest_source_bytes": 424141,
              "source_files_sampled": 537,
              "oversized_source_files": 9
            },
            "components": [
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                "points": 27,
                "status": "partial",
                "details": [
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                    }
                  }
                ],
                "max_points": 45
              },
              {
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                "detail": "9/537 source files over 60KB",
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                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
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                      "sampled": 537,
                      "oversized": 9
                    }
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                ],
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              }
            ]
          },
          {
            "key": "ai_interfaces",
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            "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",
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                "status": "met",
                "details": [
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                  }
                ],
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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"
  },
  "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"
}

Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.

Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.12.0 — metodología completa · wiki de métricas.

Cómo se sitúa un resultado dentro del registro general: estadísticas agregadasPyPI.