Registro público
Informe de salud del softwareesquema 0.11.0 · métricas 1.13.0 · 2026-07-15 09:44 UTC

robocurve / inspect-robots

Evaluation framework for VLA / physical-AI models: define a benchmark once, run any policy on any robot or sim. (The Inspect AI for robotics.)

PythonMIT★ 5 estrellas⑂ 4 forksdesde jun 2026Ver en GitHub ↗

robocurve/inspect-robots tiene un índice de salud de 66 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (96/100) y la más baja, Security (50/100). Se actualizó por última vez hoy. Una sola persona concentra la mayor parte del trabajo reciente.

66
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.

66
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

robocurveOrganización
7 seguidores7 repositorios públicosdesde jun 2026

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
PyPIinspect-robots0.11.0-15hace 0 díasbenchmarkembodied-aievaluationphysical-airoboticsvision-language-actionvla

Métricas por categoría

Vitalidad

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

74Bueno · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
2.1/36Cadencia de commits — 3/52 semanas con commits
18/18Volumen de commits — 261 commits en el último año
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Datos de entrada utilizados
commits_last_year261
human_commit_share
days_since_last_push0
active_weeks_last_year3
Cómo se puntúa
27/27Publica versiones — 15 versiones publicadas
36/36Recencia de las versiones — última versión hace 0 días
27/27Cadencia de publicación — una versión cada ~0,1 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count15
latest_release_tagv0.11.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases0,1
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?

50Moderado · 18% del índice global
Cómo se puntúa
9.8/60Estrellas — 5 estrellas
4/25Forks — 4 forks
0/15Observadores — 0 observadores
Datos de entrada utilizados
forks4
stars5
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (MIT)
18/18Guía CONTRIBUTING
13.5/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_templateno
has_code_of_conduct
has_pull_request_template

Sostenibilidad y Gobernanza

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

57Moderado · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
4.7/22.5Distribución de commits — el principal contribuyente firma el 79% de los commits
8.1/13.5Amplitud de contribuyentes — 6 contribuyentes
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Datos de entrada utilizados
bus_factor1
contributors_sampled6
top_contributor_share0,793
Cómo se puntúa
38/46.8Resolución de issues — 81% de issues cerradas
37.1/38.3Aceptación de PR — 65/67 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — Found 0/13 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs65
open_issues6
closed_issues26
issue_closed_ratio0,812
closed_unmerged_prs2
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
6.5/25Alcance del propietario — 7 seguidores de robocurve
6.7/25Trayectoria — 7 repos públicos, cuenta de ~0 años
Datos de entrada utilizados
followers7
owner_typeOrganization
is_verified
owner_loginrobocurve
public_repos7
account_age_days19
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 0 días
20/20Historial de versiones — 15 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesinspect-robots
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

96Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 4 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 13 out of 13 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_config

Documentación

100Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://robocurve.github.io/inspect-robots/
10/10Descripción del repositorio
10/10Topics — 8 topics
10/10Wiki
Datos de entrada utilizados
topicsbenchmark, embodied-ai, evaluation, physical-ai, rerun, robotics, vision-language-action, vla
has_wiki
homepagehttps://robocurve.github.io/inspect-robots/
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
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 13 out of 13 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 0/13 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Licencia — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
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
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_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5
Excluidos de la puntuación (sin datos o no aplicable): signed_releases. 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.

67Moderado · 0% del índice global
Cómo se puntúa
45/45Instrucciones para agentes — CLAUDE.md, src/inspect_robots/CLAUDE.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_filesCLAUDE.md, src/inspect_robots/CLAUDE.md
agent_instruction_max_bytes6974
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
0/18Arranque con un solo comando
22/22Pruebas automatizadas
11/11Configuración de lint / formato
11/11Verificación estática de tipos — plugins/inspect-robots-agent/src/inspect_robots_agent/py.typed, plugins/inspect-robots-isaacsim/src/inspect_robots_isaacsim/py.typed, src/inspect_robots/py.typed
10/10Entorno reproducible — 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
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_config
typecheck_configsplugins/inspect-robots-agent/src/inspect_robots_agent/py.typed, plugins/inspect-robots-isaacsim/src/inspect_robots_isaacsim/py.typed, src/inspect_robots/py.typed
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
27/45Código verificable por tipos — Python con configuración de verificación de tipos (plugins/inspect-robots-agent/src/inspect_robots_agent/py.typed, plugins/inspect-robots-isaacsim/src/inspect_robots_isaacsim/py.typed, src/inspect_robots/py.typed)
53.5/55Tamaños de archivo manejables — 2/75 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes87.155
source_files_sampled75
oversized_source_files2
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — examples
Datos de entrada utilizados
example_dirsexamples
has_mcp_signalno
api_schema_files

Datos clave

5estrellas de GitHub
6contribuidores
261commits en los últimos 12 meses
0días desde el último push
15versiones publicadas
1factor bus
6issues abiertas
PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 5.0 / 10
5.0agregado

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 · 2026-07-15 09:44 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests13 out of 13 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 0/13 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
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
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 1
RegistroPaqueteRestricción de versiónManifiesto
PyPInumpy>=1.24pyproject.toml
Todas las dependencias 92

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 3 paquetes directos y 89 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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Informe JSON sin procesar legible por máquina
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            "reason": "no dangerous workflow patterns detected",
            "documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#dangerous-workflow"
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            "reason": "no update tool detected",
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            "reason": "project is not fuzzed",
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            "reason": "license file detected",
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            "reason": "security policy file detected",
            "documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#security-policy"
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            "reason": "no releases found",
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            "documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#token-permissions"
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            "reason": "0 existing vulnerabilities detected",
            "documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#vulnerabilities"
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      "key": "overall",
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      "name": "Overall health",
      "note": null,
      "notes": [],
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      "inputs": {
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        "community": 50,
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        "engineering": 96
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    "categories": [
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        "metrics": [
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                "key": "verified_domain",
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              {
                "key": "owner_reach",
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                "max_points": 25
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              {
                "key": "track_record",
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                "key": "published_resolvable",
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                "key": "cii_best_practices",
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                "key": "code_review",
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                "key": "dependency_update_tool",
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              {
                "key": "fuzzing",
                "name": "Fuzzing",
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                "key": "maintained",
                "name": "Maintained",
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                "key": "packaging",
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                "key": "pinned_dependencies",
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                "key": "sast",
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                "key": "security_policy",
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                "key": "signed_releases",
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                "max_points": 7.5
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                "key": "token_permissions",
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
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          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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        "key": "ai_readiness",
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        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
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  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-15T09:44:56.123352Z",
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}

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.