Registro público
Informe de salud del softwareesquema 0.11.0 · métricas 1.13.0 · 2026-07-17 08:23 UTC

pydantic / pydantic-ai

AI Agent Framework, the Pydantic way

PythonMIT★ 18.607 estrellas⑂ 2378 forksdesde jun 2024Ver en GitHub ↗

pydantic/pydantic-ai tiene un índice de salud de 88 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Vitality (100/100) y la más baja, Security (71/100). Se actualizó por última vez hoy. 4 personas concentran la mayor parte del trabajo reciente.

88
global / 100
Excelente

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.

88
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

PydanticOrganización
2883 seguidores79 repositorios públicosdesde ago 2022

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
PyPIclai2.12.020.528220hace 0 días
PyPIpydantic-ai-examples2.12.0-284hace 0 días
PyPIpydantic-ai-slim2.12.0173.728.429284hace 0 días
PyPIpydantic-evals2.12.0-239hace 0 días
PyPIpydantic-graph2.12.0112.745.288268hace 0 días
PyPIpydantic-ai2.12.0-290hace 0 días

Métricas por categoría

Vitalidad

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

100Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
36/36Cadencia de commits — 52/52 semanas con commits
18/18Volumen de commits — 1550 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year1550
human_commit_share
days_since_last_push0
active_weeks_last_year52
Cómo se puntúa
27/27Publica versiones — 100 versiones publicadas
36/36Recencia de las versiones — última versión hace 0 días
27/27Cadencia de publicación — una versión cada ~1,1 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count100
latest_release_tagv2.12.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases1,1
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?

90Excelente · 18% del índice global
Cómo se puntúa
60/60Estrellas — 18.607 estrellas
25/25Forks — 2378 forks
11.4/15Observadores — 115 observadores
Datos de entrada utilizados
forks2378
stars18.607
watchers115
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
0/13.5Código 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_conductno
has_pull_request_template
Cómo se puntúa
80/80Descargas mensuales — 286.494.245 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagesclai, pydantic-ai-examples, pydantic-ai-slim, pydantic-evals, pydantic-graph, pydantic-ai
dependents
ecosystemspypi
total_downloads
monthly_downloads286.494.245
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?

84Bueno · 24% del índice global
Cómo se puntúa
43.2/54Factor bus — la mitad de los commits recae en 4 contribuyente(s)
17.5/22.5Distribución de commits — el principal contribuyente firma el 22% de los commits
13.5/13.5Amplitud de contribuyentes — 100 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 39 contributing companies or organizations
Datos de entrada utilizados
bus_factor4
contributors_sampled100
top_contributor_share0,221
Cómo se puntúa
40.2/46.8Resolución de issues — 86% de issues cerradas
25.5/38.3Aceptación de PR — 2433/3644 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs2433
open_issues358
closed_issues2182
issue_closed_ratio0,859
closed_unmerged_prs1211
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
24.9/25Alcance del propietario — 2883 seguidores de pydantic
20.9/25Trayectoria — 79 repos públicos, cuenta de ~3 años
Datos de entrada utilizados
followers2883
owner_typeOrganization
is_verified
owner_loginpydantic
public_repos79
account_age_days1438
Cómo se puntúa
25/25Publicado y resoluble — 6 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 0 días
20/20Historial de versiones — 290 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesclai, pydantic-ai-examples, pydantic-ai-slim, pydantic-evals, pydantic-graph, pydantic-ai
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

92Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 23 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 — 30 out of 30 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

90Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://pydantic.dev/pydantic-ai
10/10Descripción del repositorio
10/10Topics — 5 topics
0/10Wiki
Datos de entrada utilizados
topicsagent-framework, pydantic, python, genai, llm
has_wikino
homepagehttps://pydantic.dev/pydantic-ai
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?

71Bueno · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
2.5/2.5CI-Tests — 30 out of 30 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 39 contributing companies or organizations
0/10Dangerous-Workflow — dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Licencia — license file detected
7.5/7.5Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
4.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
4/5SAST — SAST tool is not run on all commits -- score normalized to 8
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — sin datos
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
0/7.5Vulnerabilities — 13 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7,1
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, 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.

81Bueno · 0% del índice global
Cómo se puntúa
45/45Instrucciones para agentes — .github/workflows/AGENTS.md, .github/workflows/CLAUDE.md, AGENTS.md, CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/agent.md, docs/api/agent.md, pydantic_ai_slim/pydantic_ai/AGENTS.md, pydantic_ai_slim/pydantic_ai/CLAUDE.md, pydantic_ai_slim/pydantic_ai/capabilities/AGENTS.md, pydantic_ai_slim/pydantic_ai/durable_exec/AGENTS.md, pydantic_ai_slim/pydantic_ai/models/AGENTS.md, pydantic_ai_slim/pydantic_ai/models/CLAUDE.md, pydantic_ai_slim/pydantic_ai/native_tools/AGENTS.md, pydantic_ai_slim/pydantic_ai/native_tools/CLAUDE.md, pydantic_ai_slim/pydantic_ai/profiles/AGENTS.md, pydantic_ai_slim/pydantic_ai/providers/AGENTS.md, pydantic_ai_slim/pydantic_ai/toolsets/AGENTS.md, pydantic_ai_slim/pydantic_ai/ui/AGENTS.md, pydantic_ai_slim/pydantic_ai/ui/CLAUDE.md, tests/AGENTS.md, tests/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_files.github/workflows/AGENTS.md, .github/workflows/CLAUDE.md, AGENTS.md, CLAUDE.md, docs/AGENTS.md, docs/CLAUDE.md, docs/agent.md, docs/api/agent.md, pydantic_ai_slim/pydantic_ai/AGENTS.md, pydantic_ai_slim/pydantic_ai/CLAUDE.md, pydantic_ai_slim/pydantic_ai/capabilities/AGENTS.md, pydantic_ai_slim/pydantic_ai/durable_exec/AGENTS.md, pydantic_ai_slim/pydantic_ai/models/AGENTS.md, pydantic_ai_slim/pydantic_ai/models/CLAUDE.md, pydantic_ai_slim/pydantic_ai/native_tools/AGENTS.md, pydantic_ai_slim/pydantic_ai/native_tools/CLAUDE.md, pydantic_ai_slim/pydantic_ai/profiles/AGENTS.md, pydantic_ai_slim/pydantic_ai/providers/AGENTS.md, pydantic_ai_slim/pydantic_ai/toolsets/AGENTS.md, pydantic_ai_slim/pydantic_ai/ui/AGENTS.md, pydantic_ai_slim/pydantic_ai/ui/CLAUDE.md, tests/AGENTS.md, tests/CLAUDE.md
agent_instruction_max_bytes64.738
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
18/18Arranque con un solo comando — Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato
11/11Verificación estática de tipos — examples/pydantic_ai_examples/py.typed, pydantic_ai_slim/pydantic_ai/py.typed, pydantic_evals/pydantic_evals/py.typed, pydantic_graph/pydantic_graph/py.typed
10/10Entorno reproducible — lockfile
0/10Práctica demostrada con agentes — sin datos
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
9/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 9
Datos de entrada utilizados
has_nixno
has_tests
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_config
typecheck_configsexamples/pydantic_ai_examples/py.typed, pydantic_ai_slim/pydantic_ai/py.typed, pydantic_evals/pydantic_evals/py.typed, pydantic_graph/pydantic_graph/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes. Los pesos restantes se han renormalizado.
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (examples/pydantic_ai_examples/py.typed, pydantic_ai_slim/pydantic_ai/py.typed, pydantic_evals/pydantic_evals/py.typed, pydantic_graph/pydantic_graph/py.typed)
50.3/55Tamaños de archivo manejables — 49/577 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes889.559
source_files_sampled577
oversized_source_files49
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
20/20Servidor MCP
40/40Ejemplos ejecutables — examples
Datos de entrada utilizados
example_dirsexamples
has_mcp_signal
api_schema_files

Datos clave

18.607estrellas de GitHub
100contribuidores
1550commits en los últimos 12 meses
0días desde el último push
100versiones publicadas
4factor bus
358issues abiertas
PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 7.1 / 10
7.1agregado

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 · 2026-07-17 08:22 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
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 39 contributing companies or organizations
0Dangerous-Workflowdangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
9Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 9
8SASTSAST tool is not run on all commits -- score normalized to 8
10Security-Policysecurity policy file detected
n/dSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
0Vulnerabilities13 existing vulnerabilities detected
Dependencias directas 4
RegistroPaqueteRestricción de versiónManifiesto
PyPIhttpx>=0.27pydantic_graph/pyproject.toml
PyPIlogfire-api>=3.14.1pydantic_graph/pyproject.toml
PyPIpydantic>=2.12pydantic_graph/pyproject.toml
PyPItyping-inspection>=0.4.0pydantic_graph/pyproject.toml
Todas las dependencias 366

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 6 paquetes directos y 360 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIhttpx0.28.1directa
PyPIlogfire-apidirecta
PyPIlogfire-api4.37.0directa
PyPIpydanticdirecta
PyPIpydantic2.13.4directa
PyPItyping-inspection0.4.2directa
PyPIag-ui-protocol0.1.19indirecta
PyPIaiofile3.9.0indirecta
PyPIaiohappyeyeballs2.6.1indirecta
PyPIaiohttp3.14.1indirecta
PyPIaiolimiter1.2.1indirecta
PyPIaiosignal1.4.0indirecta
PyPIaiosqlite0.21.0indirecta
PyPIalembic1.17.2indirecta
PyPIalgoliasearch4.44.1indirecta
PyPIamplitude-analytics1.2.3indirecta
PyPIannotated-doc0.0.4indirecta
PyPIannotated-types0.7.0indirecta
PyPIanthropic0.109.0indirecta
PyPIanyio4.14.1indirecta
PyPIapprise1.9.6indirecta
PyPIargcomplete3.6.3indirecta
PyPIasgi-lifespan2.1.0indirecta
PyPIasgiref3.11.0indirecta
PyPIast-serialize0.5.0indirecta
PyPIasttokens2.4.1indirecta
PyPIasync-timeout5.0.1indirecta
PyPIasyncpg0.31.0indirecta
PyPIattrs25.4.0indirecta
PyPIaudioop-lts0.2.2indirecta
PyPIauthlib1.7.2indirecta
PyPIbabel2.17.0indirecta
PyPIbackports-tarfile1.2.0indirecta
PyPIbackrefs6.1indirecta
PyPIbeartype0.22.9indirecta
PyPIbeautifulsoup44.14.3indirecta
PyPIblack26.5.1indirecta
PyPIboto31.42.63indirecta
PyPIboto3-stubs1.42.63indirecta
PyPIbotocore1.42.63indirecta
PyPIbotocore-stubs1.42.41indirecta
PyPIbrotli1.2.0indirecta
PyPIbrotlicffi1.2.0.0indirecta
PyPIburner-redis0.1.7indirecta
PyPIcachetools6.2.4indirecta
PyPIcaio0.9.25indirecta
PyPIcairocffi1.7.1indirecta
PyPIcairosvg2.9.0indirecta
PyPIcertifi2025.11.12indirecta
PyPIcffi2.0.0indirecta
PyPIchardet5.2.0indirecta
PyPIcharset-normalizer3.4.4indirecta
PyPIclick8.1.8indirecta
PyPIcloudpickle3.1.2indirecta
PyPIcohere5.20.6indirecta
PyPIcolorama0.4.6indirecta
PyPIcoolname2.2.0indirecta
PyPIcoverage7.13.0indirecta
PyPIcronsim2.7indirecta
PyPIcryptography49.0.0indirecta
PyPIcssselect20.8.0indirecta
PyPIcuda-bindings13.1.1indirecta
PyPIcuda-pathfinder1.3.4indirecta
PyPIcuda-toolkit13.0.2indirecta
PyPIcyclopts4.15.0indirecta
PyPIdatasets4.4.2indirecta
PyPIdateparser1.2.2indirecta
PyPIdbos2.10.0indirecta
PyPIddgs9.10.0indirecta
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PyPIdevtools0.12.2indirecta
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PyPIdnspython2.8.0indirecta
PyPIdocker7.1.0indirecta
PyPIdocstring-parser0.17.0indirecta
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PyPIduckdb1.4.3indirecta
PyPIduckduckgo-search8.1.1indirecta
PyPIemail-validator2.3.0indirecta
PyPIeval-type-backport0.3.1indirecta
PyPIexa-py2.15.0indirecta
PyPIexceptiongroup1.3.1indirecta
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PyPIexecuting2.2.1indirecta
PyPIfake-useragent2.2.0indirecta
PyPIfastapi0.138.1indirecta
PyPIfastavro1.12.1indirecta
PyPIfastmcp3.4.2indirecta
PyPIfastmcp-slim3.4.2indirecta
PyPIffmpeg-python0.2.0indirecta
PyPIfilelock3.20.3indirecta
PyPIfrozenlist1.8.0indirecta
PyPIfsspec2025.10.0indirecta
PyPIfuture1.0.0indirecta
PyPIgenai-prices0.0.70indirecta
PyPIghp-import2.1.0indirecta
PyPIgoogle-auth2.49.1indirecta
PyPIgoogle-genai1.70.0indirecta
PyPIgoogleapis-common-protos1.72.0indirecta
PyPIgradio6.19.0indirecta
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PyPIgriffe-warnings-deprecated1.1.1indirecta
PyPIgriffelib2.0.0indirecta
PyPIgroovy0.1.2indirecta
PyPIgroq0.25.0indirecta
PyPIgrpcio1.76.0indirecta
PyPIgrpclib0.4.7indirecta
PyPIh110.16.0indirecta
PyPIh24.3.0indirecta
PyPIhatchlingindirecta
PyPIhf-gradio0.4.1indirecta
PyPIhf-xet1.2.0indirecta
PyPIhf-xet1.4.3indirecta
PyPIhpack4.1.0indirecta
PyPIhttpcore1.0.9indirecta
PyPIhttpcore22.3.0indirecta
PyPIhttpx-sse0.4.3indirecta
PyPIhttpx22.3.0indirecta
PyPIhuggingface-hub1.16.1indirecta
PyPIhuggingface-hub1.3.4indirecta
PyPIhumanize4.15.0indirecta
PyPIhyperframe6.1.0indirecta
PyPIidna3.16indirecta
PyPIimportlib-metadata8.7.1indirecta
PyPIiniconfig2.3.0indirecta
PyPIinline-snapshot0.34.2indirecta
PyPIjaraco-classes3.4.0indirecta
PyPIjaraco-context6.1.0indirecta
PyPIjaraco-functools4.4.0indirecta
PyPIjeepney0.9.0indirecta
PyPIjinja23.1.6indirecta
PyPIjinja2-humanize-extension0.4.0indirecta
PyPIjiter0.12.0indirecta
PyPIjmespath1.0.1indirecta
PyPIjoblib1.5.3indirecta
PyPIjoserfc1.7.1indirecta
PyPIjsonpatch1.33indirecta
PyPIjsonpath-python1.1.5indirecta
PyPIjsonpointer3.0.0indirecta
PyPIjsonref1.1.0indirecta
PyPIjsonschema4.25.1indirecta
PyPIjsonschema-path0.3.4indirecta
PyPIjsonschema-specifications2025.9.1indirecta
PyPIkeyring25.7.0indirecta
PyPIlangchain-core1.4.0indirecta
PyPIlangchain-protocol0.0.15indirecta
PyPIlangchain-text-splitters1.1.2indirecta
PyPIlangsmith0.9.3indirecta
PyPIlibrt0.11.0indirecta
PyPIlogfire4.37.0indirecta
PyPIlxml6.1.1indirecta
PyPImako1.3.12indirecta
PyPImarkdown3.10indirecta
PyPImarkdown-it-py3.0.0indirecta
PyPImarkdownify1.2.2indirecta
PyPImarkupsafe2.1.5indirecta
PyPImcp1.25.0indirecta
PyPImdformat0.7.22indirecta
PyPImdformat-tables1.0.0indirecta
PyPImdurl0.1.2indirecta
PyPImergedeep1.3.4indirecta
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                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
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                ],
                "max_points": 7.5
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              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "GitHub workflow tokens follow principle of least privilege",
                "points": 7.5,
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                "details": [],
                "max_points": 7.5
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "13 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
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            ]
          },
          {
            "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": {}
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                "Russia",
                "Iran",
                "North Korea"
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              "assessed_self_published_locations": 10
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            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "key": "machine_readable_docs_llms_txt",
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            ]
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            "key": "ai_verify_loop",
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            "notes": [
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                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
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                "code": "weights_renormalized",
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            ],
            "value": 96,
            "inputs": {
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              "has_tests": true,
              "lockfiles": [
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              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
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              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
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              ],
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              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
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                "key": "one_command_bootstrap",
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                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
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                "max_points": 18
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              {
                "key": "automated_tests",
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              },
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                "key": "lint_format_config",
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                "points": 11,
                "status": "met",
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              },
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                "key": "static_type_checking",
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                "details": [
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                ],
                "max_points": 11
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              {
                "key": "reproducible_environment",
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                "points": 10,
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                "details": [
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              {
                "key": "demonstrated_agent_practice",
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                "status": "excluded",
                "details": [
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                    "params": {}
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                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
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                "points": 5,
                "status": "partial",
                "details": [
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                    "code": "dependency_bot_config_only",
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                ],
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              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 9",
                "points": 9,
                "status": "partial",
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            ]
          },
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            "key": "ai_code_legibility",
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            "name": "Code legibility for models",
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            "notes": [],
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            "inputs": {
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            "inputs": {
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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."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [],
  "report_type": "repository",
  "generated_at": "2026-07-17T08:23:35.441238Z",
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  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/pydantic/pydantic-ai.svg",
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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.