Registro público
Informe de salud del softwareesquema 0.11.0 · métricas 1.13.0 · 2026-07-17 15:22 UTC

greenbone / ospd-openvas

ospd-openvas is an OSP server implementation to allow GVM to remotely control an OpenVAS Scanner

PythonAGPL-3.0★ 80 estrellas⑂ 63 forksdesde jun 2018Ver en GitHub ↗

greenbone/ospd-openvas tiene un índice de salud de 72 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Engineering Quality (80/100) y la más baja, AI Readiness (44/100). Se actualizó por última vez hace 3 días. Una sola persona concentra la mayor parte del trabajo reciente.

72
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.

72
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

GreenboneOrganización
1310 seguidores68 repositorios públicosdesde sept 2017

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

Ecosistemas de paquetes

RegistroPaqueteVersiónDescargas / mesVersionesÚltima publicaciónEtiquetas
PyPIospd-openvas22.10.3-36hace 3 díasopenvasgreenbone-vulnerability-managementvulnerability-scanningospopen-scanner-protocol
Gogithub.com/greenbone/ospd-openvasv22.10.3+incompatible-38hace 3 días

Métricas por categoría

Vitalidad

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

77Bueno · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 3 días
9.7/36Cadencia de commits — 14/52 semanas con commits
14/18Volumen de commits — 35 commits en el último año
8/10OpenSSF Scorecard: Maintained — 8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
Datos de entrada utilizados
commits_last_year35
human_commit_share
days_since_last_push3
active_weeks_last_year14
Cómo se puntúa
27/27Publica versiones — 38 versiones publicadas
36/36Recencia de las versiones — última versión hace 3 días
19.8/27Cadencia de publicación — una versión cada ~90,3 días
8/10OpenSSF Scorecard: Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
Datos de entrada utilizados
releases_count38
latest_release_tagv22.10.3
releases_from_tagsno
days_since_latest_release3
mean_days_between_releases90,3

Comunidad y Adopción

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

54Moderado · 18% del índice global
Cómo se puntúa
30.8/60Estrellas — 80 estrellas
14.9/25Forks — 63 forks
6.4/15Observadores — 15 observadores
Datos de entrada utilizados
forks63
stars80
watchers15
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (AGPL-3.0)
0/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributingno
has_issue_templateno
has_code_of_conductno
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?

74Bueno · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
11.1/22.5Distribución de commits — el principal contribuyente firma el 50% de los commits
13.5/13.5Amplitud de contribuyentes — 31 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 6 contributing companies or organizations
Datos de entrada utilizados
bus_factor1
contributors_sampled31
top_contributor_share0,505
Cómo se puntúa
44.2/46.8Resolución de issues — 94% de issues cerradas
33.6/38.3Aceptación de PR — 915/1042 PR decididos fusionados
10.5/15OpenSSF Scorecard: Code-Review — Found 12/17 approved changesets -- score normalized to 7
Datos de entrada utilizados
merged_prs915
open_issues3
closed_issues52
issue_closed_ratio0,945
closed_unmerged_prs127
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
22.4/25Alcance del propietario — 1310 seguidores de greenbone
25/25Trayectoria — 68 repos públicos, cuenta de ~8 años
Datos de entrada utilizados
followers1310
owner_typeOrganization
is_verified
owner_logingreenbone
public_repos68
account_age_days3227
Cómo se puntúa
25/25Publicado y resoluble — 2 paquete(s) en go, pypi
35/35Recencia de publicación — última publicación hace 3 días
20/20Historial de versiones — 38 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesospd-openvas, github.com/greenbone/ospd-openvas
ecosystemsgo, pypi
any_deprecatedno
min_days_since_publish3

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

80Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 13 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — .pylintrc
0/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 24 out of 24 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_configno
Cómo se puntúa
30/30README
25/25Directorio de documentación
0/15Sitio de documentación / página del proyecto
10/10Descripción del repositorio
10/10Topics — 5 topics
0/10Wiki
Datos de entrada utilizados
topicspython, base, openvas, techops, tooling
has_wikino
homepage
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?

72Bueno · 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 — 24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
5.2/7.5Code-Review — Found 12/17 approved changesets -- score normalized to 7
2.5/2.5Contributors — project has 6 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
6/7.5Maintained — 8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
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
5/5Security-Policy — security policy file detected
6/7.5Signed-Releases — 5 out of the last 5 releases have a total of 5 signed artifacts.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
5.2/7.5Vulnerabilities — 3 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate7,2
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.

44En riesgo · 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 — smoketest/Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — .pylintrc
0/11Verificación estática de tipos
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
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfilesgo.sum, poetry.lock
has_dockerfile
typed_languageno
bootstrap_filessmoketest/Makefile
has_devcontainerno
has_linter_config
typecheck_configs
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
0/45Código verificable por tipos — Python sin configuración de verificación de tipos
55/55Tamaños de archivo manejables — 0/95 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes56.303
source_files_sampled95
oversized_source_files0

Datos clave

80estrellas de GitHub
31contribuidores
35commits en los últimos 12 meses
3días desde el último push
38versiones publicadas
1factor bus
3issues abiertas
Go, PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 7.2 / 10
7.2agregado

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 · 2026-07-17 15:21 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-Tests24 out of 24 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 12/17 approved changesets -- score normalized to 7
10Contributorsproject has 6 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
8Maintained8 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 8
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
8Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7Vulnerabilities3 existing vulnerabilities detected
Dependencias directas 10
RegistroPaqueteRestricción de versiónManifiesto
PyPIredis>=4.5.0,<7.2.0pyproject.toml
PyPIpsutil>=5.5.1,<8.0.0pyproject.toml
PyPIpackaging>=20.4,<27.0pyproject.toml
PyPIlxml>=4.5.2,<7.0.0pyproject.toml
PyPIdefusedxml>=0.6,<0.8pyproject.toml
PyPIdeprecated^1.2.10pyproject.toml
PyPIpaho-mqtt>=1.6,<3pyproject.toml
PyPIpython-gnupg>=0.4.8,<0.6.0pyproject.toml
Gogithub.com/eclipse/paho.golangv0.10.0smoketest/go.mod
Gogithub.com/google/uuidv1.3.0smoketest/go.mod
Todas las dependencias 70

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 12 paquetes directos y 58 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
Gogithub.com/eclipse/paho.golang0.10.0directa
Gogithub.com/eclipse/paho.golangv0.10.0directa
Gogithub.com/google/uuid1.3.0directa
Gogithub.com/google/uuidv1.3.0directa
PyPIdefusedxml0.7.1directa
PyPIdeprecated1.3.1directa
PyPIlxml6.1.1directa
PyPIpackaging26.2directa
PyPIpaho-mqtt2.1.0directa
PyPIpsutil7.2.2directa
PyPIpython-gnupg0.5.6directa
PyPIredis7.0.1directa
Gogithub.com/davecgh/go-spew1.1.1indirecta
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Gogithub.com/stretchr/objxv0.1.0indirecta
Gogithub.com/stretchr/testifyv1.7.0indirecta
Gogolang.org/x/sync0.0.0-20210220032951-036812b2e83cindirecta
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Gogolang.org/x/xerrorsv0.0.0-20191204190536-9bdfabe68543indirecta
Gogopkg.in/check.v1v0.0.0-20161208181325-20d25e280405indirecta
Gogopkg.in/yaml.v33.0.1indirecta
Gogopkg.in/yaml.v3v3.0.1indirecta
PyPIanyio4.12.1indirecta
PyPIastroid3.3.11indirecta
PyPIasync-timeout5.0.1indirecta
PyPIautohooks25.11.0indirecta
PyPIautohooks-plugin-black23.10.0indirecta
PyPIautohooks-plugin-pylint23.10.0indirecta
PyPIblack25.11.0indirecta
PyPIcertifi2026.1.4indirecta
PyPIclick8.1.8indirecta
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PyPIh110.16.0indirecta
PyPIh24.3.0indirecta
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PyPIhttpcore1.0.9indirecta
PyPIhttpx0.28.1indirecta
PyPIhyperframe6.1.0indirecta
PyPIidna3.15indirecta
PyPIimportlib-metadata8.7.1indirecta
PyPIisort6.1.0indirecta
PyPImarkdown-it-py3.0.0indirecta
PyPImccabe0.7.0indirecta
PyPImdurl0.1.2indirecta
PyPImypy-extensions1.1.0indirecta
PyPIpathspec1.0.4indirecta
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PyPIpontos26.2.0indirecta
PyPIpygments2.20.0indirecta
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                "key": "dependency_update_tool",
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                "key": "fuzzing",
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
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          },
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            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 6
            },
            "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": 44,
        "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": 73,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "go.sum",
                "poetry.lock"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
                "smoketest/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "smoketest/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "smoketest/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": ".pylintrc",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".pylintrc"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "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 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 55,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 56303,
              "source_files_sampled": 95,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/95 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 95,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-17T15:22:23.683801Z",
  "schema_version": "0.11.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/g/greenbone/ospd-openvas.svg",
  "full_name": "greenbone/ospd-openvas",
  "license_state": "standard",
  "license_spdx": "AGPL-3.0"
}

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 v0.11.0 — metodología completa · wiki de métricas.

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