Registro público
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-26 07:41 UTC

debbiemarkslab / EVcouplings

Evolutionary couplings from protein and RNA sequence alignments

Jupyter Notebook · PythonLicencia propia★ 313 estrellas⑂ 83 forksdesde jul 2016Ver en GitHub ↗

debbiemarkslab/EVcouplings tiene un índice de salud de 54 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (72/100) y la más baja, Vitality (31/100). Se actualizó por última vez hace 96 días. Una sola persona concentra la mayor parte del trabajo reciente.

54
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.

54
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

Debora Marks LabOrganización
135 seguidores33 repositorios públicosdesde sept 2014

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
PyPIevcouplings0.2.1-7hace 627 díasanalysiscouplingsevolutionary

Métricas por categoría

Vitalidad

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

31En riesgo · 22% del índice global
Cómo se puntúa
9.9/36Recencia de push — último push hace 96 días
2.1/36Cadencia de commits — 3/52 semanas con commits
9.7/18Volumen de commits — 11 commits en el último año
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Datos de entrada utilizados
commits_last_year11
human_commit_share1
days_since_last_push96
active_weeks_last_year3
Cómo se puntúa
27/27Publica versiones — 7 versiones publicadas
7.2/36Recencia de las versiones — última versión hace 627 días
5.4/27Cadencia de publicación — una versión cada ~436,7 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count7
latest_release_tagv0.2.1
releases_from_tagsno
days_since_latest_release627
mean_days_between_releases436,7
Excluidos de la puntuación (sin datos o no aplicable): OpenSSF Scorecard: Signed-Releases. Los pesos restantes se han renormalizado.

Comunidad y Adopción

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

55Moderado · 18% del índice global
Cómo se puntúa
40.5/60Estrellas — 313 estrellas
16/25Forks — 83 forks
7.7/15Observadores — 25 observadores
Datos de entrada utilizados
forks83
stars313
watchers25
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
16.9/22.5Licencia — archivo de licencia presente, no es una licencia reconocida
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_license
has_contributingno
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno

Sostenibilidad y Gobernanza

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

61Moderado · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
8.2/22.5Distribución de commits — el principal contribuyente firma el 63% de los commits
12.2/13.5Amplitud de contribuyentes — 9 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Datos de entrada utilizados
bus_factor1
contributors_sampled9
top_contributor_share0,634
Cómo se puntúa
32.9/46.8Resolución de issues — 70% de issues cerradas
31.3/38.3Aceptación de PR — 108/132 PR decididos fusionados
1.5/15OpenSSF Scorecard: Code-Review — Found 1/6 approved changesets -- score normalized to 1
Datos de entrada utilizados
merged_prs108
open_issues59
closed_issues140
issue_closed_ratio0,704
closed_unmerged_prs24
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
15.3/25Alcance del propietario — 135 seguidores de debbiemarkslab
23.2/25Trayectoria — 33 repos públicos, cuenta de ~11 años
Datos de entrada utilizados
followers135
owner_typeOrganization
is_verified
owner_logindebbiemarkslab
public_repos33
account_age_days4316
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
14/35Recencia de publicación — última publicación hace 627 días
20/20Historial de versiones — 7 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesevcouplings
ecosystemspypi
any_deprecatedno
min_days_since_publish627

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

72Bueno · 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
6/20OpenSSF Scorecard: CI-Tests — 2 out of 6 merged PRs checked by a CI test -- score normalized to 3
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 — http://evcouplings.org
10/10Descripción del repositorio
10/10Topics — 4 topics
10/10Wiki
Datos de entrada utilizados
topicsstructure-prediction, 3d-structure, protein, protein-complexes
has_wiki
homepagehttp://evcouplings.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?

50Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
0.8/2.5CI-Tests — 2 out of 6 merged PRs checked by a CI test -- score normalized to 3
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 1/6 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 10 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5Licencia — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — sin datos
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 — sin datos
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3,7
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, packaging, signed_releases. Los pesos restantes se han renormalizado.
Cómo se puntúa
35/35Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido
25/25Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages39
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:evcouplings@0.2.1 —lo que arrastra la instalación del paquete publicado—: 39 paquetes. No se analiza la alcanzabilidad.

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.

34En 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)
13.3/40Historial de commits legible — 25 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,25
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
18/18Arranque con un solo comando — docs/Makefile
22/22Pruebas automatizadas
0/11Configuración de lint / formato
0/11Verificación estática de tipos
0/10Entorno reproducible
0/10Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100
0/8Mantenimiento automatizado — no se observan actualizaciones automáticas de dependencias
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Cómo se puntúa
0/45Código verificable por tipos — Jupyter Notebook sin configuración de verificación de tipos
53.6/55Tamaños de archivo manejables — 2/81 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languageJupyter Notebook
largest_source_bytes263.767
source_files_sampled81
oversized_source_files2
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — example, notebooks
Datos de entrada utilizados
example_dirsexample, notebooks
has_mcp_signalno
api_schema_files

Datos clave

313estrellas de GitHub
9contribuidores
11commits en los últimos 12 meses
96días desde el último push
7versiones publicadas
1factor bus
59issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

Más detalle

Historial de estrellas y forks 0 ★ / 83 ⇿
0Estrellas
83Forks
6Versiones

Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.

0204060807732017-092022-022026-07
Mayor 0Menor 0Parche 6

Cada punto abarca 9 días.

OpenSSF Scorecard 3.7 / 10
3.7agregado

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 · 2026-07-26 07:41 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
3CI-Tests2 out of 6 merged PRs checked by a CI test -- score normalized to 3
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 1/6 approved changesets -- score normalized to 1
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/dPackagingpackaging workflow not 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
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 18
RegistroPaqueteRestricción de versiónManifiesto
PyPIbilliardpyproject.toml
PyPIbiopython>=1.84pyproject.toml
PyPIbokehpyproject.toml
PyPIclickpyproject.toml
PyPIfilelockpyproject.toml
PyPIjinja2pyproject.toml
PyPImatplotlibpyproject.toml
PyPImsgpackpyproject.toml
PyPInumbapyproject.toml
PyPInumpypyproject.toml
PyPIpandaspyproject.toml
PyPIpsutilpyproject.toml
PyPIrequestspyproject.toml
PyPIruamel.yaml<0.18pyproject.toml
PyPIscikit-learnpyproject.toml
PyPIscipypyproject.toml
PyPIseabornpyproject.toml
PyPIsetuptools>=18.2pyproject.toml
Todas las dependencias 18

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 18 paquetes directos y 0 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIbilliarddirecta
PyPIbiopythondirecta
PyPIbokehdirecta
PyPIclickdirecta
PyPIfilelockdirecta
PyPIjinja2directa
PyPImatplotlibdirecta
PyPImsgpackdirecta
PyPInumbadirecta
PyPInumpydirecta
PyPIpandasdirecta
PyPIpsutildirecta
PyPIrequestsdirecta
PyPIruamel-yamldirecta
PyPIscikit-learndirecta
PyPIscipydirecta
PyPIseaborndirecta
PyPIsetuptoolsdirecta
Avisos de dependencias 0

Instalar pypi:evcouplings@0.2.1 arrastra 39 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.

Ningún aviso conocido afecta a las dependencias evaluadas.

Un aviso significa que la versión registrada en el grafo de dependencias cae dentro del rango afectado de un aviso. No se analiza la alcanzabilidad, y el grafo incluye fijaciones de desarrollo y prueba: un hallazgo puede referirse al utillaje y no al software distribuido.

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                "key": "openssf_scorecard_contributors",
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                "key": "owner_reach",
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                "key": "fuzzing",
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                "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": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "dependency_advisories",
            "band": "excellent",
            "name": "Dependency advisories",
            "note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:evcouplings@0.2.1 runtime dependency closure — what installing the published package pulls in — 39 packages. Reachability is not analyzed.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "no_advisories_left_outstanding"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              },
              {
                "code": "advisories_scope_published",
                "params": {
                  "package": "pypi:evcouplings@0.2.1",
                  "assessed": 39
                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "source": "osv",
              "advisories": 0,
              "affected_packages": 0,
              "assessed_packages": 39,
              "unassessed_packages": 0,
              "affected_by_severity": "none",
              "direct_affected_packages": 0
            },
            "components": [
              {
                "key": "direct_dependencies_free_of_known_advisories",
                "name": "Direct dependencies free of known advisories",
                "detail": "no direct dependency carries a known advisory",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "no_direct_advisories",
                    "params": {}
                  }
                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
              },
              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
                "detail": "no advisory carries a publication date",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "advisories_no_publication_date",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "malicious_dependencies",
            "band": "excellent",
            "name": "Malicious dependencies",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "source": "osv",
              "meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
              "packages": [],
              "red_flag": false,
              "assessed_packages": 39,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
            },
            "components": [
              {
                "key": "no_dependency_reported_as_a_malicious_package",
                "name": "No dependency reported as a malicious package",
                "detail": "no dependency is reported as a malicious package",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "no_malicious_dependencies",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          },
          {
            "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": 11
            },
            "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": 34,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 13,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0.25,
              "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": "25 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 13.3,
                "status": "partial",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 25,
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "at_risk",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "docs/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": false,
              "typecheck_configs": [],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "docs/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs/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": 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": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no agent-authored commits among the last 100",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_authored_commits",
                    "params": {
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_dependency_automation",
                    "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": 54,
            "inputs": {
              "primary_language": "Jupyter Notebook",
              "largest_source_bytes": 263767,
              "source_files_sampled": 81,
              "oversized_source_files": 2
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Jupyter Notebook without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Jupyter Notebook"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "2/81 source files over 60KB",
                "points": 53.6,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 81,
                      "oversized": 2
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "example",
                "notebooks"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "example, notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "example, notebooks"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-26T07:41:44.719075Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/debbiemarkslab/EVcouplings.svg",
  "full_name": "debbiemarkslab/EVcouplings",
  "license_state": "custom",
  "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 v0.27.0 — metodología completa · wiki de métricas.

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