Registro públicoExcelente
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-30 22:15 UTC
mne-tools / mne-python
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
mne-tools/mne-python tiene un índice de salud de 89 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Engineering Quality (96/100) y la más baja, AI Readiness (64/100). Se actualizó por última vez hoy. 3 personas concentran la mayor parte del trabajo reciente.
89
global / 100Índice 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.
89
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)
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
MNE tools for MEG and EEG data analysisOrganización
312 seguidores49 repositorios públicosdesde ene 2011
Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.
Ecosistemas de paquetes
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación | Etiquetas |
|---|---|---|---|---|---|---|
| PyPI | mne | 1.12.1 | 424.271 | 86 | hace 101 días | ecogeegmegbrainfnirsneuroimagingneuroscience |
Métricas por categoría
Vitalidad
¿Está vivo el proyecto: se escribe código y se publican versiones?
93
Actividad de desarrollo
100Excelente
Cómo se puntúa
| 36/36 | Recencia de push — último push hace 0 días |
| 36/36 | Cadencia de commits — 52/52 semanas con commits |
| 18/18 | Volumen de commits — 452 commits en el último año |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10 |
Datos de entrada utilizados
| commits_last_year | 452 |
| human_commit_share | 0,87 |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
Disciplina de publicación
82Bueno
Cómo se puntúa
| 27/27 | Publica versiones — 64 versiones publicadas |
| 27/36 | Recencia de las versiones — última versión hace 101 días |
| 19.8/27 | Cadencia de publicación — una versión cada ~81,2 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
Datos de entrada utilizados
| releases_count | 64 |
| latest_release_tag | v1.12.1 |
| releases_from_tags | no |
| days_since_latest_release | 101 |
| mean_days_between_releases | 81,2 |
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?
93
Popularidad y adopción
93Excelente
Cómo se puntúa
| 57.4/60 | Estrellas — 3475 estrellas |
| 25/25 | Forks — 1576 forks |
| 10.6/15 | Observadores — 83 observadores |
Datos de entrada utilizados
| forks | 1576 |
| stars | 3475 |
| watchers | 83 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Salud de la comunidad
92Excelente
Cómo se puntúa
| 22.5/22.5 | README |
| 22.5/22.5 | Licencia — licencia reconocida (BSD-3-Clause) |
| 18/18 | Guía CONTRIBUTING |
| 13.5/13.5 | Código de conducta |
| 0/7.2 | Plantilla de issues |
| 6.3/6.3 | Plantilla de PR |
Datos de entrada utilizados
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | sí |
| has_pull_request_template | sí |
Adopción en el ecosistema (descargas)
94Excelente
Cómo se puntúa
| 75/80 | Descargas mensuales — 424.271 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
Datos de entrada utilizados
| packages | mne |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 424.271 |
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?
83
Cómo se puntúa
| 36/54 | Factor bus — la mitad de los commits recae en 3 contribuyente(s) |
| 16.3/22.5 | Distribución de commits — el principal contribuyente firma el 28% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 97 contribuyentes |
| 10/10 | OpenSSF Scorecard: Contributors — project has 61 contributing companies or organizations |
Datos de entrada utilizados
| bus_factor | 3 |
| contributors_sampled | 97 |
| top_contributor_share | 0,276 |
Capacidad de respuesta a issues y PR
87Excelente
Cómo se puntúa
| 42.1/46.8 | Resolución de issues — 90% de issues cerradas |
| 33.2/38.3 | Aceptación de PR — 7630/8788 PR decididos fusionados |
| 12/15 | OpenSSF Scorecard: Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
Datos de entrada utilizados
| merged_prs | 7630 |
| open_issues | 520 |
| closed_issues | 4656 |
| issue_closed_ratio | 0,9 |
| closed_unmerged_prs | 1158 |
Propiedad y custodia
72Bueno
Cómo se puntúa
| 30/30 | Respaldo de la propiedad — propiedad de una organización |
| 0/20 | Dominio verificado |
| 17.9/25 | Alcance del propietario — 312 seguidores de mne-tools |
| 24.4/25 | Trayectoria — 49 repos públicos, cuenta de ~15 años |
Datos de entrada utilizados
| followers | 312 |
| owner_type | Organization |
| is_verified | — |
| owner_login | mne-tools |
| public_repos | 49 |
| account_age_days | 5664 |
Mantenimiento de paquetes
100Excelente
Cómo se puntúa
| 25/25 | Publicado y resoluble — 1 paquete(s) en pypi |
| 35/35 | Recencia de publicación — última publicación hace 101 días |
| 20/20 | Historial de versiones — 86 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
Datos de entrada utilizados
| packages | mne |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 101 |
Calidad de Ingeniería
¿Existen unas prácticas mínimas de ingeniería y documentación?
96
Prácticas de ingeniería
94Excelente
Cómo se puntúa
| 24/24 | Flujos de trabajo de CI — 9 flujo(s) de trabajo |
| 24/24 | Pruebas presentes |
| 16/16 | Configuración de linter |
| 9.6/9.6 | Hooks de pre-commit |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
Datos de entrada utilizados
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | sí |
| has_precommit_config | sí |
Documentación
100Excelente
Cómo se puntúa
| 30/30 | README |
| 25/25 | Directorio de documentación |
| 15/15 | Sitio de documentación / página del proyecto — https://mne.tools |
| 10/10 | Descripción del repositorio |
| 10/10 | Topics — 12 topics |
| 10/10 | Wiki |
Datos de entrada utilizados
| topics | python, neuroscience, electroencephalography, magnetoencephalography, electrocorticography, machine-learning, statistics, visualization, eeg, meg, ecog, neuroimaging |
| has_wiki | sí |
| homepage | https://mne.tools |
| has_readme | sí |
| has_docs_dir | sí |
| has_description | sí |
Seguridad
¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?
82
Postura de seguridad
78Bueno
Cómo se puntúa
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — sin datos |
| 2.5/2.5 | CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 1.8/2.5 | CII-Best-Practices — badge detected: Silver |
| 6/7.5 | Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
| 2.5/2.5 | Contributors — project has 61 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Licencia — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 4.5/5 | SAST — SAST tool detected but not run on all commits |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — sin datos |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Datos de entrada utilizados
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 7,8 |
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, signed_releases. Los pesos restantes se han renormalizado.
Avisos de dependencias
100Excelente
Cómo se puntúa
| 35/35 | Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido |
| 25/25 | Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido |
| 0/40 | Sin avisos pendientes — ningún aviso tiene fecha de publicación |
Datos de entrada utilizados
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 24 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
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:mne@1.12.1 —lo que arrastra la instalación del paquete publicado—: 24 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.
64
Contexto y guía para agentes
85Excelente
Cómo se puntúa
| 45/45 | Instrucciones para agentes — AGENTS.md, CLAUDE.md |
| 0/15 | Documentación legible por máquinas (llms.txt) |
| 40/40 | Historial de commits legible — 78 de 87 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo) |
Datos de entrada utilizados
| has_llms_txt | no |
| legible_history_share | 0,897 |
| agent_instruction_files | AGENTS.md, CLAUDE.md |
| agent_instruction_max_bytes | 7654 |
Cómo se puntúa
| 18/18 | Arranque con un solo comando — Makefile, doc/Makefile, tools/dev/Makefile |
| 22/22 | Pruebas automatizadas |
| 11/11 | Configuración de lint / formato |
| 0/11 | Verificación estática de tipos |
| 0/10 | Entorno reproducible |
| 2/10 | Práctica demostrada con agentes — 1 de los últimos 100 commits con autoría o crédito de agente |
| 8/8 | Mantenimiento automatizado — 5 de los últimos 100 commits son actualizaciones automáticas de dependencias |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Datos de entrada utilizados
| has_nix | no |
| has_tests | sí |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | Makefile, doc/Makefile, tools/dev/Makefile |
| has_devcontainer | no |
| has_linter_config | sí |
| typecheck_configs | — |
| agent_commit_share | 0,01 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0,05 |
Legibilidad del código para modelos
52Moderado
Cómo se puntúa
| 0/45 | Código verificable por tipos — Python sin configuración de verificación de tipos |
| 52/55 | Tamaños de archivo manejables — 50/908 archivos fuente de más de 60 KB |
Datos de entrada utilizados
| primary_language | Python |
| largest_source_bytes | 219.130 |
| source_files_sampled | 908 |
| oversized_source_files | 50 |
Interfaces legibles por máquina
40En riesgo
Cómo se puntúa
| 0/40 | Esquema de API (OpenAPI/GraphQL/proto) |
| 0/20 | Servidor MCP |
| 40/40 | Ejemplos ejecutables — examples, sample |
Datos de entrada utilizados
| example_dirs | examples, sample |
| has_mcp_signal | no |
| api_schema_files | — |
Datos clave
3475estrellas de GitHub
97contribuidores
452commits en los últimos 12 meses
0días desde el último push
64versiones publicadas
3factor bus
520issues 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 ★ / 1576 ⇿
0Estrellas
1576Forks
51Versiones
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.
Solo se muestra el historial más reciente: este repositorio supera la ventana de recopilación, por lo que no se captura el historial más antiguo.
Mayor 1Menor 18Parche 32
Cada punto abarca 7 días.
OpenSSF Scorecard 7.8 / 10
7.8agregado
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| n/d | Branch-Protection | internal 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 |
| 10 | CI-Tests | 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 7 | CII-Best-Practices | badge detected: Silver |
| 8 | Code-Review | Found 26/29 approved changesets -- score normalized to 8 |
| 10 | Contributors | project has 61 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 19 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 9 | SAST | SAST tool detected but not run on all commits |
| 10 | Security-Policy | security policy file detected |
| n/d | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Dependencias directas 10
| Registro | Paquete | Restricción de versión | Manifiesto |
|---|---|---|---|
| PyPI | decorator | >= 5.1 | pyproject.toml |
| PyPI | jinja2 | >= 3.1 | pyproject.toml |
| PyPI | lazy_loader | >= 0.3 | pyproject.toml |
| PyPI | matplotlib | >= 3.9 | pyproject.toml |
| PyPI | numpy | >= 2.0, < 3 | pyproject.toml |
| PyPI | packaging | — | pyproject.toml |
| PyPI | pooch | >= 1.5 | pyproject.toml |
| PyPI | scipy | >= 1.14 | pyproject.toml |
| PyPI | tqdm | >= 4.66 | pyproject.toml |
| PyPI | typing-extensions | >= 4.15 | pyproject.toml |
Todas las dependencias 64
Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 8 paquetes directos y 56 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.
| Registro | Paquete | Versión | Relación |
|---|---|---|---|
| PyPI | decorator | — | directa |
| PyPI | jinja2 | — | directa |
| PyPI | lazy-loader | — | directa |
| PyPI | matplotlib | — | directa |
| PyPI | numpy | — | directa |
| PyPI | pooch | — | directa |
| PyPI | scipy | — | directa |
| PyPI | tqdm | — | directa |
| PyPI | antio | — | indirecta |
| PyPI | curryreader | — | indirecta |
| PyPI | dipy | — | indirecta |
| PyPI | docutils | — | indirecta |
| PyPI | edfio | — | indirecta |
| PyPI | filelock | — | indirecta |
| PyPI | h5io | — | indirecta |
| PyPI | h5py | — | indirecta |
| PyPI | hatchling | — | indirecta |
| PyPI | imageio | — | indirecta |
| PyPI | imageio-ffmpeg | — | indirecta |
| PyPI | intersphinx-registry | — | indirecta |
| PyPI | ipython | — | indirecta |
| PyPI | joblib | — | indirecta |
| PyPI | memory-profiler | — | indirecta |
| PyPI | mffpy | — | indirecta |
| PyPI | mne-qt-browser | — | indirecta |
| PyPI | nibabel | — | indirecta |
| PyPI | nilearn | — | indirecta |
| PyPI | nitime | — | indirecta |
| PyPI | numba | — | indirecta |
| PyPI | numpydoc | — | indirecta |
| PyPI | openmeeg | — | indirecta |
| PyPI | openneuro-py | — | indirecta |
| PyPI | pandas | — | indirecta |
| PyPI | pillow | — | indirecta |
| PyPI | pip | — | indirecta |
| PyPI | pydata-sphinx-theme | — | indirecta |
| PyPI | pygments | — | indirecta |
| PyPI | pyobjc-framework-cocoa | — | indirecta |
| PyPI | pyqt6 | — | indirecta |
| PyPI | pyqt6-qt6 | — | indirecta |
| PyPI | pyside6 | — | indirecta |
| PyPI | pytest | — | indirecta |
| PyPI | pytest-cov | — | indirecta |
| PyPI | pytest-qt | — | indirecta |
| PyPI | pytest-timeout | — | indirecta |
| PyPI | pytest-xdist | — | indirecta |
| PyPI | python-picard | — | indirecta |
| PyPI | pyvista | — | indirecta |
| PyPI | pyvistaqt | — | indirecta |
| PyPI | pyzmq | — | indirecta |
| PyPI | qdarkstyle | — | indirecta |
| PyPI | rcssmin | — | indirecta |
| PyPI | refleak | — | indirecta |
| PyPI | ruff | — | indirecta |
| PyPI | scikit-learn | — | indirecta |
| PyPI | seaborn | — | indirecta |
| PyPI | selenium | — | indirecta |
| PyPI | sphinx | — | indirecta |
| PyPI | sphinx-gallery | — | indirecta |
| PyPI | sphinxcontrib-bibtex | — | indirecta |
| PyPI | sphinxcontrib-towncrier | — | indirecta |
| PyPI | statsmodels | — | indirecta |
| PyPI | trame-vuetify | — | indirecta |
| PyPI | vtk | — | indirecta |
Avisos de dependencias 0
Instalar pypi:mne@1.12.1 arrastra 24 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.
Informe JSON sin procesar legible por máquina
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"published_at": "2026-04-07T19:35:14Z"
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"tag": "v1.11.0",
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"published_at": "2025-11-21T19:34:02Z"
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"published_at": "2025-08-11T14:16:42Z"
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"published_at": "2025-07-15T16:36:20Z"
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"tag": "v1.9.0",
"kind": "minor",
"published_at": "2024-12-18T21:22:26Z"
},
{
"tag": "v1.8.0",
"kind": "minor",
"published_at": "2024-08-19T02:12:47Z"
},
{
"tag": "v1.7.1",
"kind": "patch",
"published_at": "2024-06-14T22:41:47Z"
},
{
"tag": "v1.7.0",
"kind": "minor",
"published_at": "2024-04-19T18:02:55Z"
},
{
"tag": "v1.6.1",
"kind": "patch",
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"note": null,
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"inputs": {
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{
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{
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"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"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": "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:mne@1.12.1 runtime dependency closure — what installing the published package pulls in — 24 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:mne@1.12.1",
"assessed": 24
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
"source": "osv",
"advisories": 0,
"affected_packages": 0,
"assessed_packages": 24,
"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": 24,
"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": 14
},
"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": 64,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "excellent",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 85,
"inputs": {
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"legible_history_share": 0.897,
"agent_instruction_files": [
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"CLAUDE.md"
],
"agent_instruction_max_bytes": 7654
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "AGENTS.md, CLAUDE.md",
"points": 45,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "AGENTS.md, CLAUDE.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": "78 of 87 human commits state their intent (structured subject or explanatory body)",
"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
"params": {
"legible": 78,
"sampled": 87
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "moderate",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 61,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [
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"doc/Makefile",
"tools/dev/Makefile"
],
"has_devcontainer": false,
"has_linter_config": true,
"typecheck_configs": [],
"agent_commit_share": 0.01,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0.05
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": "Makefile, doc/Makefile, tools/dev/Makefile",
"points": 18,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
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}
],
"max_points": 18
},
{
"key": "automated_tests",
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"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 11,
"status": "met",
"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": "1 of the last 100 commits agent-authored or agent-credited",
"points": 2,
"status": "partial",
"details": [
{
"code": "agent_authored_commits",
"params": {
"count": 1,
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "5 of the last 100 commits are automated dependency updates",
"points": 8,
"status": "met",
"details": [
{
"code": "dependency_bot_commits",
"params": {
"count": 5,
"sampled": 100
}
}
],
"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": 52,
"inputs": {
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"largest_source_bytes": 219130,
"source_files_sampled": 908,
"oversized_source_files": 50
},
"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": "50/908 source files over 60KB",
"points": 52,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 908,
"oversized": 50
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples",
"sample"
],
"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": "examples, sample",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples, sample"
}
}
],
"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": "2026-07-30T22:15:03.022222Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/mne-tools/mne-python.svg",
"full_name": "mne-tools/mne-python",
"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 v0.27.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.