Registro público
Informe de salud del softwareesquema 0.14.0 · métricas 1.13.0 · 2026-07-19 07:19 UTC

mbari-org / aidata

(ETL) Extract, transform, load/download and augment images and annotations for detection, clustering or classification workflows

PythonSin licencia detectada★ 7 estrellas⑂ 2 forksdesde mar 2024Ver en GitHub ↗

mbari-org/aidata tiene un índice de salud de 62 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Vitality (86/100) y la más baja, Community & Adoption (29/100). Se actualizó por última vez hace 4 días. Una sola persona concentra la mayor parte del trabajo reciente.

62
global / 100
Moderado

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.

62
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

63 seguidores135 repositorios públicosdesde abr 2018

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
PyPImbari-aidata1.79.0204269hace 4 días

Métricas por categoría

Vitalidad

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

86Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 4 días
20.1/36Cadencia de commits — 29/52 semanas con commits
18/18Volumen de commits — 138 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year138
human_commit_share
days_since_last_push4
active_weeks_last_year29
Cómo se puntúa
27/27Publica versiones — 100 versiones publicadas
36/36Recencia de las versiones — última versión hace 4 días
27/27Cadencia de publicación — una versión cada ~2,7 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count100
latest_release_tagv1.79.0
releases_from_tagsno
days_since_latest_release4
mean_days_between_releases2,7

Comunidad y Adopción

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

29Crítico · 18% del índice global
Cómo se puntúa
12.6/60Estrellas — 7 estrellas
0/25Forks — 2 forks
4.3/15Observadores — 7 observadores
Datos de entrada utilizados
forks2
stars7
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
0/22.5Licencia — no se detectó ningún archivo de licencia
0/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
0/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_licenseno
has_contributingno
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno
Cómo se puntúa
44.1/80Descargas mensuales — 2042 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagesmbari-aidata
dependents
ecosystemspypi
total_downloads
monthly_downloads2042
Excluidos de la puntuación (sin datos o no aplicable): Dependientes en el registro. Los pesos restantes se han renormalizado.

Sostenibilidad y Gobernanza

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

63Moderado · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
0.7/22.5Distribución de commits — el principal contribuyente firma el 97% de los commits
6.8/13.5Amplitud de contribuyentes — 5 contribuyentes
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Datos de entrada utilizados
bus_factor1
contributors_sampled5
top_contributor_share0,968
Cómo se puntúa
42.6/46.8Resolución de issues — 91% de issues cerradas
35.2/38.3Aceptación de PR — 35/38 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — Found 0/26 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs35
open_issues3
closed_issues31
issue_closed_ratio0,912
closed_unmerged_prs3
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
13/25Alcance del propietario — 63 seguidores de mbari-org
25/25Trayectoria — 135 repos públicos, cuenta de ~8 años
Datos de entrada utilizados
followers63
owner_typeOrganization
is_verified
owner_loginmbari-org
public_repos135
account_age_days3007
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 4 días
20/20Historial de versiones — 69 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesmbari-aidata
ecosystemspypi
any_deprecatedno
min_days_since_publish4

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

81Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 2 flujo(s) de trabajo
24/24Pruebas presentes
0/16Configuración de linter
0/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 8 out of 8 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentación

100Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://docs.mbari.org/internal/ai/data
10/10Descripción del repositorio
10/10Topics — 4 topics
10/10Wiki
Datos de entrada utilizados
topicsai, database, machine-learning, etl
has_wiki
homepagehttps://docs.mbari.org/internal/ai/data
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?

40En riesgo · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 8 out of 8 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
0/7.5Code-Review — Found 0/26 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
0/2.5Licencia — license file not detected
7.5/7.5Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 42 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate4

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.

65Moderado · 0% del índice global
Cómo se puntúa
45/45Instrucciones para agentes — AGENTS.md
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_filesAGENTS.md
agent_instruction_max_bytes3044
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 — justfile
22/22Pruebas automatizadas
0/11Configuración de lint / formato
0/11Verificación estática de tipos
10/10Entorno reproducible — Dockerfile, lockfile
0/10Práctica demostrada con agentes — sin datos
0/8Mantenimiento automatizado — sin datos
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfilespoetry.lock
has_dockerfile
typed_languageno
bootstrap_filesjustfile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes, Mantenimiento automatizado. 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 — 0/49 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes37.125
source_files_sampled49
oversized_source_files0

Datos clave

7estrellas de GitHub
5contribuidores
138commits en los últimos 12 meses
4días desde el último push
100versiones publicadas
1factor bus
3issues abiertas
PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 4.0 / 10
4.0agregado

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 · 2026-07-19 07:18 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests8 out of 8 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/26 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
0Licenselicense file not detected
10Maintained30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
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.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities42 existing vulnerabilities detected
Dependencias directas 20
RegistroPaqueteRestricción de versiónManifiesto
PyPIredis5.0.7pyproject.toml
PyPItator1.2.3pyproject.toml
PyPIephem>=4.1.6pyproject.toml
PyPImoviepy>=2.1.1pyproject.toml
PyPIopencv-contrib-python4.11.0.86pyproject.toml
PyPIpytz>=2024.1pyproject.toml
PyPIpiexif>=1.1.3pyproject.toml
PyPIclick>=8.1.7pyproject.toml
PyPItqdm4.67.1pyproject.toml
PyPIrequests>=2.32.3pyproject.toml
PyPIpascal-voc-writer>=0.1.4pyproject.toml
PyPIalbumentations>=1.4.15pyproject.toml
PyPIalbucore>=0.0.16pyproject.toml
PyPIpandas^2.0pyproject.toml
PyPIpyarrow^15.0pyproject.toml
PyPInumpy>=1.24,<2pyproject.toml
PyPItorch2.2.0pyproject.toml
PyPItorchvision0.17.0pyproject.toml
PyPItransformers>=4.42.4,<6.0.0pyproject.toml
PyPIpytest^9.1.1pyproject.toml
Todas las dependencias 90

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 20 paquetes directos y 70 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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PyPIpytz2025.2directa
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PyPIrequests2.33.0directa
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                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "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 not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "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": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "42 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"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 1
            },
            "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": 65,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "good",
            "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": 75,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [
                "AGENTS.md"
              ],
              "agent_instruction_max_bytes": 3044
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "AGENTS.md",
                "points": 45,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "AGENTS.md"
                    }
                  }
                ],
                "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": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 61,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "poetry.lock"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
                "justfile"
              ],
              "has_devcontainer": false,
              "has_linter_config": false,
              "typecheck_configs": [],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "justfile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "justfile"
                    }
                  }
                ],
                "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": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "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": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "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": 37125,
              "source_files_sampled": 49,
              "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": "0/49 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 49,
                      "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": "2026-07-19T07:19:05.222988Z",
  "schema_version": "0.14.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/mbari-org/aidata.svg",
  "full_name": "mbari-org/aidata",
  "license_state": "absent",
  "license_spdx": null
}

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 v0.14.0 — metodología completa · wiki de métricas.

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