Registro público
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-24 02:11 UTC

SampleEnvironment / secop-ophyd

Integration of the SECoP field layer onto ophyd

PythonGPL-3.0★ 2 estrellas⑂ 1 forkdesde oct 2023Ver en GitHub ↗

SampleEnvironment/secop-ophyd tiene un índice de salud de 59 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (87/100) y la más baja, Community & Adoption (24/100). Se actualizó por última vez hace 6 días. Una sola persona concentra la mayor parte del trabajo reciente.

59
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.

59
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

2 seguidores15 repositorios públicosdesde jul 2017

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

Ecosistemas de paquetes

RegistroPaqueteVersiónDescargas / mesVersionesÚltima publicación
PyPIsecop-ophyd0.19.3-19hace 9 días

Métricas por categoría

Vitalidad

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

77Bueno · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 6 días
10.4/36Cadencia de commits — 15/52 semanas con commits
13.1/18Volumen de commits — 28 commits en el último año
2/10OpenSSF Scorecard: Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
Datos de entrada utilizados
commits_last_year28
human_commit_share1
days_since_last_push6
active_weeks_last_year15
Cómo se puntúa
27/27Publica versiones — 34 versiones publicadas
36/36Recencia de las versiones — última versión hace 9 días
27/27Cadencia de publicación — una versión cada ~31,6 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count34
latest_release_tagv0.19.3
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases31,6
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?

24Crítico · 18% del índice global
Cómo se puntúa
0/60Estrellas — 2 estrellas
0/25Forks — 1 forks
1.7/15Observadores — 3 observadores
Datos de entrada utilizados
forks1
stars2
watchers3
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (GPL-3.0)
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?

52Moderado · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
0/22.5Distribución de commits — el principal contribuyente firma el 100% de los commits
1.4/13.5Amplitud de contribuyentes — 1 contribuyentes
0/10OpenSSF Scorecard: Contributors — project has 0 contributing companies or organizations -- score normalized to 0
Datos de entrada utilizados
bus_factor1
contributors_sampled1
top_contributor_share1
Cómo se puntúa
27.5/46.8Resolución de issues — 59% de issues cerradas
36.6/38.3Aceptación de PR — 45/47 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs45
open_issues7
closed_issues10
issue_closed_ratio0,588
closed_unmerged_prs2
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
3.4/25Alcance del propietario — 2 seguidores de SampleEnvironment
20.8/25Trayectoria — 15 repos públicos, cuenta de ~9 años
Datos de entrada utilizados
followers2
owner_typeOrganization
is_verified
owner_loginSampleEnvironment
public_repos15
account_age_days3300
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 9 días
20/20Historial de versiones — 19 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagessecop-ophyd
ecosystemspypi
any_deprecatedno
min_days_since_publish9

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

87Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 1 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — .flake8
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests — 24 out of 25 merged PRs checked by a CI test -- score normalized to 9
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_config
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://sampleenvironment.github.io/secop-ophyd/
10/10Descripción del repositorio
0/10Topics
0/10Wiki
Datos de entrada utilizados
topics
has_wikino
homepagehttps://sampleenvironment.github.io/secop-ophyd/
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?

52Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
2.2/2.5CI-Tests — 24 out of 25 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
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
1.5/7.5Maintained — 3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
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 — 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_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, 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
0/25Dependencias indirectas libres de avisos conocidos — el conjunto transitivo no es separable de las dependencias de desarrollo y prueba en este alcance
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages152
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Dependencias indirectas libres de avisos conocidos, Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejaron 152 dependencias resueltas con OSV. Este repositorio no publica ningún paquete que el índice resuelva, por lo que se evaluó en su lugar el grafo de dependencias del repositorio. Ese grafo mezcla fijaciones de desarrollo y prueba con las dependencias distribuidas, de modo que solo se puntúan las dependencias declaradas en tiempo de ejecución; los hallazgos transitivos se informan como contexto y quedan excluidos de la puntuación. 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.

56Moderado · 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)
22.4/40Historial de commits legible — 42 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,42
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
18/18Arranque con un solo comando — docs/Makefile, makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — .flake8
11/11Verificación estática de tipos — .mypy.ini
10/10Entorno reproducible — lockfile
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
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile, makefile
has_devcontainerno
has_linter_config
typecheck_configs.mypy.ini
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (.mypy.ini)
55/55Tamaños de archivo manejables — 0/28 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes37.296
source_files_sampled28
oversized_source_files0

Datos clave

2estrellas de GitHub
1contribuidores
28commits en los últimos 12 meses
6días desde el último push
34versiones publicadas
1factor bus
7issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:secop-ophyd@0.19.3; advisories assessed against the repository dependency graph instead

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 · 2026-07-24 02:11 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
9CI-Tests24 out of 25 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
2Maintained3 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 2
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
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 5
RegistroPaqueteRestricción de versiónManifiesto
PyPIophyd-async(>0.18,<=0.19.3)pyproject.toml
PyPIfrappy-core>= 0.20.8pyproject.toml
PyPIblackpyproject.toml
PyPIJinja2pyproject.toml
PyPIautoflakepyproject.toml
Todas las dependencias 152

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 5 paquetes directos y 147 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIautoflake2.3.3directa
PyPIblack26.5.1directa
PyPIfrappy-core0.20.8directa
PyPIjinja23.1.6directa
PyPIophyd-async0.19.3directa
PyPIaccessible-pygments0.0.5indirecta
PyPIalabaster1.0.0indirecta
PyPIannotated-types0.7.0indirecta
PyPIappnope0.1.4indirecta
PyPIast-serialize0.6.0indirecta
PyPIastroid3.3.11indirecta
PyPIasttokens3.0.1indirecta
PyPIattrs26.1.0indirecta
PyPIbabel2.18.0indirecta
PyPIbeautifulsoup44.15.0indirecta
PyPIbluesky1.15.1indirecta
PyPIcertifi2026.6.17indirecta
PyPIcffi2.1.0indirecta
PyPIcfgv3.5.0indirecta
PyPIcharset-normalizer3.4.7indirecta
PyPIclick8.4.2indirecta
PyPIcolorama0.4.6indirecta
PyPIcolorlog6.10.1indirecta
PyPIcomm0.2.3indirecta
PyPIcompress-pickle2.1.0indirecta
PyPIcontourpy1.3.3indirecta
PyPIcoverage7.15.0indirecta
PyPIcycler0.12.1indirecta
PyPIdebugpy1.8.21indirecta
PyPIdecorator5.3.1indirecta
PyPIdistlib0.4.3indirecta
PyPIdocutils0.22.4indirecta
PyPIevent-model1.24.0indirecta
PyPIexecuting2.2.1indirecta
PyPIfilelock3.29.6indirecta
PyPIflake87.3.0indirecta
PyPIflexcache0.3indirecta
PyPIflexparser0.4indirecta
PyPIfonttools4.63.0indirecta
PyPIhistorydict1.2.6indirecta
PyPIidentify2.6.19indirecta
PyPIidna3.18indirecta
PyPIimagesize2.0.0indirecta
PyPIiniconfig2.3.0indirecta
PyPIipykernel7.3.0indirecta
PyPIipython9.15.0indirecta
PyPIipython-pygments-lexers1.1.1indirecta
PyPIisort8.0.1indirecta
PyPIjedi0.20.0indirecta
PyPIjsonschema4.26.0indirecta
PyPIjsonschema-specifications2025.9.1indirecta
PyPIjupyter-client8.9.1indirecta
PyPIjupyter-core5.9.1indirecta
PyPIkiwisolver1.5.0indirecta
PyPIlibrt0.12.0indirecta
PyPIlockfile0.12.2indirecta
PyPIlz44.4.5indirecta
PyPImarkdown-it-py4.2.0indirecta
PyPImarkupsafe3.0.3indirecta
PyPImatplotlib3.11.0indirecta
PyPImatplotlib-inline0.2.2indirecta
PyPImccabe0.7.0indirecta
PyPImdit-py-plugins0.6.1indirecta
PyPImdurl0.1.2indirecta
PyPImlzlog0.5.0indirecta
PyPImsgpack1.2.1indirecta
PyPImsgpack-numpy0.4.8indirecta
PyPImypy2.1.0indirecta
PyPImypy-extensions1.1.0indirecta
PyPImyst-parser5.1.0indirecta
PyPInest-asyncio21.7.2indirecta
PyPInetworkx3.6.1indirecta
PyPInodeenv1.10.0indirecta
PyPInumpy2.4.6indirecta
PyPInumpy2.5.1indirecta
PyPInumpydoc1.10.0indirecta
PyPIopentelemetry-api1.43.0indirecta
PyPIophyd1.11.2indirecta
PyPIpackaging26.2indirecta
PyPIparso0.8.7indirecta
PyPIpathspec1.1.1indirecta
PyPIpep8-naming0.15.1indirecta
PyPIpexpect4.9.0indirecta
PyPIpillow12.3.0indirecta
PyPIpint0.25.3indirecta
PyPIplatformdirs4.10.0indirecta
PyPIpluggy1.6.0indirecta
PyPIpre-commit4.6.0indirecta
PyPIprompt-toolkit3.0.52indirecta
PyPIpsutil7.2.2indirecta
PyPIptyprocess0.7.0indirecta
PyPIpure-eval0.2.3indirecta
PyPIpycodestyle2.14.0indirecta
PyPIpycparser3.0indirecta
PyPIpydantic2.13.4indirecta
PyPIpydantic-core2.46.4indirecta
PyPIpydantic-numpy8.0.1indirecta
PyPIpydata-sphinx-theme0.19.0indirecta
PyPIpyflakes3.4.0indirecta
PyPIpygments2.20.0indirecta
PyPIpyparsing3.3.2indirecta
PyPIpyserial3.5indirecta
PyPIpytest9.1.1indirecta
PyPIpytest-asyncio1.4.0indirecta
PyPIpytest-cov7.1.0indirecta
PyPIpytest-xprocess1.0.2indirecta
PyPIpython-daemon3.1.2indirecta
PyPIpython-dateutil2.9.0.post0indirecta
PyPIpython-discovery1.4.3indirecta
PyPIpython-dotenv1.2.2indirecta
PyPIpytokens0.4.1indirecta
PyPIpyyaml6.0.3indirecta
PyPIpyzmq27.1.0indirecta
PyPIreferencing0.37.0indirecta
PyPIrequests2.34.2indirecta
PyPIroman-numerals4.1.0indirecta
PyPIrpds-py2026.6.3indirecta
PyPIruamel-yaml0.18.17indirecta
PyPIruamel-yaml-clib0.2.15indirecta
PyPIscanspec1.0.0indirecta
PyPIsemver3.0.4indirecta
PyPIsix1.17.0indirecta
PyPIsnowballstemmer3.1.1indirecta
PyPIsoupsieve2.8.4indirecta
PyPIsphinx9.0.4indirecta
PyPIsphinx9.1.0indirecta
PyPIsphinx-autodoc20.5.0indirecta
PyPIsphinx-click6.2.0indirecta
PyPIsphinx-copybutton0.5.2indirecta
PyPIsphinx-design0.7.0indirecta
PyPIsphinxcontrib-applehelp2.0.0indirecta
PyPIsphinxcontrib-devhelp2.0.0indirecta
PyPIsphinxcontrib-htmlhelp2.1.0indirecta
PyPIsphinxcontrib-jsmath1.0.1indirecta
PyPIsphinxcontrib-mermaid2.0.2indirecta
PyPIsphinxcontrib-qthelp2.0.0indirecta
PyPIsphinxcontrib-serializinghtml2.0.0indirecta
PyPIstack-data0.6.3indirecta
PyPIstamina26.1.0indirecta
PyPItenacity9.1.4indirecta
PyPItomli2.4.1indirecta
PyPItoolz1.1.0indirecta
PyPItornado6.5.7indirecta
PyPItqdm4.68.4indirecta
PyPItraitlets5.15.1indirecta
PyPItyping-extensions4.16.0indirecta
PyPItyping-inspection0.4.2indirecta
PyPIurllib32.7.0indirecta
PyPIvelocity-profile1.0.0indirecta
PyPIvirtualenv21.6.0indirecta
PyPIwcwidth0.8.2indirecta
PyPIwheel0.47.0indirecta
Avisos de dependencias 0

Este repositorio no publica ningún paquete que el índice resuelva, así que se evaluó su propio grafo de dependencias — 152 paquetes, que incluyen también fijaciones de desarrollo y prueba que nunca se distribuyen: 0 tienen avisos conocidos, de los cuales 0 son 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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                "key": "ownership_backing",
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                "key": "verified_domain",
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                "key": "owner_reach",
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                "key": "track_record",
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          {
            "key": "package_maintenance",
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              "ecosystems": "pypi",
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        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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                "key": "fuzzing",
                "name": "Fuzzing",
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                "key": "license",
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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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                "max_points": 7.5
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                "key": "vulnerabilities",
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            ]
          },
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              {
                "code": "advisories_scope_repository",
                "params": {
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              },
              {
                "code": "advisories_repo_graph_caveat",
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              {
                "code": "advisories_reachability",
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            "value": 100,
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            "components": [
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                "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": [
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                    "code": "no_direct_advisories",
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                ],
                "max_points": 35
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              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "transitive set not separable from development and test dependencies in this scope",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "advisories_scope_not_separable",
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                ],
                "max_points": 25
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              {
                "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": {}
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                ],
                "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": 152,
              "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": 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": 56,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 22,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0.42,
              "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": "42 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 22.4,
                "status": "partial",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 42,
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "good",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 72,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "docs/Makefile",
                "makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                ".mypy.ini"
              ],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "docs/Makefile, makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs/Makefile, 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": ".flake8",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".flake8"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": ".mypy.ini",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".mypy.ini"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "lockfile"
                    }
                  }
                ],
                "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": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 82,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 37296,
              "source_files_sampled": 28,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (.mypy.ini)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": ".mypy.ini",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/28 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 28,
                      "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": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "deps.dev does not index pypi:secop-ophyd@0.19.3; advisories assessed against the repository dependency graph instead"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-24T02:11:58.133797Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/s/SampleEnvironment/secop-ophyd.svg",
  "full_name": "SampleEnvironment/secop-ophyd",
  "license_state": "standard",
  "license_spdx": "GPL-3.0"
}

Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.

Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.27.0 — metodología completa · wiki de métricas.

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