Registro público
Informe de salud del softwareesquema 0.34.0 · métricas 2.10.0 · 2026-09-15 23:32 UTC

Smart-AI-Memory / attune-ai

Persistent memory and receipt-verified workflows for Claude Code — plugin, MCP server, and spec-driven dev framework in one pip install.

HTML · PythonApache-2.0★ 10 estrellas⑂ 2 forksdesde feb 2026Ver en GitHub ↗
TipoComplementoHerramienta de línea de comandosBibliotecaServidor MCPInterfaz webcómo se determina
#ai#claude#cost-optimization#developer-tools#llm#multi-agent#workflows#sdd#spec-driven-development#agent-memory#claude-code#claude-code-plugin#mcp#python#rag

Smart-AI-Memory/attune-ai tiene un índice de salud de 89 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Vitality (94/100) y la más baja, Community & Adoption (54/100). Se actualizó por última vez hace 1 día. Una sola persona concentra la mayor parte del trabajo reciente.

89
global / 100
Excelente

Índice de salud del software

Las métricas se agrupan en categorías ponderadas sobre una escala estandarizada de 1 a 100. El resultado global parte de su media ponderada, calibrada contra la distribución del registro público para que las bandas tengan significado percentil; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe un límite «En riesgo» de 34.

89
Excepcional93-100El nivel más alto del registro (≈ el 5% superior); cumple prácticamente todos los criterios evaluados
Excelente80-92Sólido en todos los frentes; carencias menores
Bueno65-79Saludable; carencias limitadas y manejables
Moderado50-64Aceptable con carencias notables; se recomienda revisión
Débil35-49Debilidades sustanciales en varias áreas
En riesgo20-34Debilidades significativas; su adopción exige cautela
Crítico1-19Problemas 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.

El resultado global ponderado 75 se calibra a 89 en la escala publicada del índice (calibración del registro 2026-08-02).

Titularidad

Smart AI MemoryOrganización
5 seguidores18 repositorios públicosdesde oct 2025

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
PyPIattune-ai16.4.04371179hace 6 díasaiclaudeanthropicllmai-agentmulti-agentdeveloper-toolscode-reviewsecurity-audittest-generationworkflow-automationcost-optimizationclaude-codemcpmodel-context-protocolstatic-analysiscode-qualitydevopsci-cdcli

Métricas por categoría

Vitalidad

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

94Excepcional · 21% del índice global

Actividad de desarrollo

96Excepcional
Cómo se puntúa
36/36Recencia de push — último push hace 1 días
32.5/36Cadencia de commits — 47/52 semanas con commits
18/18Volumen de commits — 4134 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year4134
human_commit_share0,71
days_since_last_push1
active_weeks_last_year47

Disciplina de publicación

90Excelente
Cómo se puntúa
27/27Publica versiones — 100 versiones publicadas
36/36Recencia de las versiones — última versión hace 6 días
27/27Cadencia de publicación — una versión cada ~2 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count100
latest_release_tagv16.4.0
releases_from_tagsno
days_since_latest_release6
mean_days_between_releases2

Comunidad y Adopción

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

54Moderado · 17% del índice global

Popularidad y adopción

16Crítico
Cómo se puntúa
15.5/60Estrellas — 10 estrellas
0/25Forks — 2 forks
0/15Observadores — 1 observadores
Datos de entrada utilizados
forks2
stars10
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Salud de la comunidad

92Excelente
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (Apache-2.0)
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_readmesí
has_licensesí
readme_badges6
has_contributingsí
has_issue_templateno
has_code_of_conductsí
readme_badge_servicesgithub.com, shields.io
has_pull_request_templatesí

Adopción en el ecosistema (descargas)

61Moderado
Cómo se puntúa
48.5/80Descargas mensuales — 4371 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagesattune-ai
dependents—
ecosystemspypi
total_downloads—
monthly_downloads4371
unverified_packages_excluded—
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?

56Moderado · 23% del índice global

Resiliencia de mantenedores (factor bus)

18Crítico
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
2.7/13.5Amplitud de contribuyentes — 2 contribuyentes
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Datos de entrada utilizados
bus_factor1
contributors_sampled2
top_contributor_share0,999

Capacidad de respuesta a issues y PR

75Bueno
Cómo se puntúa
36.5/42Resolución de issues — 87% de issues cerradas
29/30Aceptación de PR — 2400/2481 PR decididos fusionados
0/13Newcomer PR acceptance — ningún PR de un contribuyente primerizo decidido en 30 d
0/15OpenSSF Scorecard: Code-Review — Found 0/29 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs2400
open_issues6
closed_issues40
prs_merged_7d46
prs_decided_7d47
prs_merged_30d52
prs_decided_30d53
issue_closed_ratio0,87
closed_unmerged_prs81
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluidos de la puntuación (sin datos o no aplicable): Newcomer PR acceptance. Los pesos restantes se han renormalizado.

Propiedad y custodia

47Débil
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
5.6/25Alcance del propietario — 5 seguidores de Smart-AI-Memory
11.1/25Trayectoria — 18 repos públicos, cuenta de ~0 años
Datos de entrada utilizados
followers5
owner_typeOrganization
is_verifiedno
owner_loginSmart-AI-Memory
public_repos18
account_age_days324

Mantenimiento de paquetes

100Excepcional
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 6 días
20/20Historial de versiones — 179 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesattune-ai
ecosystemspypi
any_deprecatedno
min_days_since_publish6

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

92Excelente · 19% del índice global

Prácticas de ingeniería

94Excepcional
Cómo se puntúa
24/24Flujos de trabajo de CI — 31 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — eslint.config.mjs, pyproject.toml ([tool.ruff], [tool.black])
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 25 out of 25 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_cisí
has_testssí
has_editorconfigno
has_linter_configsí
has_precommit_configsí

Documentación

90Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://attune-ai.dev
10/10Descripción del repositorio
10/10Topics — 15 topics
0/10Wiki
Datos de entrada utilizados
topicsai, claude, cost-optimization, developer-tools, llm, multi-agent, workflows, sdd, spec-driven-development, agent-memory, claude-code, claude-code-plugin, mcp, python, rag
has_wikino
homepagehttps://attune-ai.dev
docs_sitehttps://attune-ai.dev
has_readmesí
has_docs_dirsí
has_descriptionsí

Seguridad

¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?

76Bueno · 16% del índice global

Postura de seguridad

70Bueno
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 — 25 out of 25 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 0/29 approved changesets -- score normalized to 0
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
0/10Dangerous-Workflow — sin datos
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — sin datos
2.5/2.5Licencia — license file detected
7.5/7.5Maintained — 30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — sin datos
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — sin datos
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated13
scorecard_versionv5.5.0
checks_inconclusive5
scorecard_aggregate7
Excluidos de la puntuación (sin datos o no aplicable): Branch-Protection, Dangerous-Workflow, Fuzzing, Packaging, Token-Permissions. Los pesos restantes se han renormalizado.

Avisos de dependencias

100Excepcional
Cómo se puntúa
35/35Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido
25/25Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages68
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:attune-ai@16.4.0 —lo que arrastra la instalación del paquete publicado—: 68 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? Tiene un peso deliberadamente pequeño (4%): las herramientas para agentes son una señal real de mantenimiento, pero un repositorio sin ninguna puede alcanzar igualmente 100/100.

91Excelente · 4% del índice global

Contexto y guía para agentes

85Excelente
Cómo se puntúa
45/45Instrucciones para agentes — .agents/AGENTS.md, .claude/CLAUDE.md, AGENTS.md, CLAUDE.md, content/features/agents.md, docs/architecture/agents.md, docs/features/agents.md, docs/how-to/agents.md, docs/reference/agents.md, plugin/help/generated/comparisons/agents.md, plugin/help/generated/concepts/agents.md, plugin/help/generated/errors/agents.md, plugin/help/generated/faqs/agents.md, plugin/help/generated/notes/agents.md, plugin/help/generated/quickstarts/agents.md, plugin/help/generated/references/agents.md, plugin/help/generated/tasks/agents.md, plugin/help/generated/tips/agents.md, plugin/help/generated/troubleshooting/agents.md, plugin/help/generated/warnings/agents.md, src/attune/commands/agent.md, website/CLAUDE.md
0/15Documentación legible por máquinas (llms.txt)
40/40Historial de commits legible — 71 de 71 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files.agents/AGENTS.md, .claude/CLAUDE.md, AGENTS.md, CLAUDE.md, content/features/agents.md, docs/architecture/agents.md, docs/features/agents.md, docs/how-to/agents.md, docs/reference/agents.md, plugin/help/generated/comparisons/agents.md, plugin/help/generated/concepts/agents.md, plugin/help/generated/errors/agents.md, plugin/help/generated/faqs/agents.md, plugin/help/generated/notes/agents.md, plugin/help/generated/quickstarts/agents.md, plugin/help/generated/references/agents.md, plugin/help/generated/tasks/agents.md, plugin/help/generated/tips/agents.md, plugin/help/generated/troubleshooting/agents.md, plugin/help/generated/warnings/agents.md, src/attune/commands/agent.md, website/CLAUDE.md
agent_instruction_max_bytes76.488

Bucle de verificación (compilación / pruebas / verificación de tipos)

95Excepcional
Cómo se puntúa
18/18Arranque con un solo comando — Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — eslint.config.mjs, pyproject.toml ([tool.ruff], [tool.black])
11/11Verificación estática de tipos — attune_redis/py.typed, vscode-extension/tsconfig.json, website/tsconfig.json
10/10Entorno reproducible — devcontainer, Dockerfile, lockfile
10/10Práctica demostrada con agentes — 57 de los últimos 100 commits con autoría o crédito de agente
8/8Mantenimiento automatizado — 8 de los últimos 100 commits son actualizaciones automáticas de dependencias
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Datos de entrada utilizados
has_nixno
has_testssí
lockfilespackage-lock.json, uv.lock
has_dockerfilesí
typed_languageno
bootstrap_filesMakefile
has_devcontainersí
has_linter_configsí
typecheck_configsattune_redis/py.typed, vscode-extension/tsconfig.json, website/tsconfig.json
agent_commit_share0,57
toolchain_manifestsplugins/jetbrains-plugin/build.gradle.kts
dependency_bot_commit_share0,08

Legibilidad del código para modelos

82Excelente
Cómo se puntúa
27/45Código verificable por tipos — HTML con configuración de verificación de tipos (attune_redis/py.typed, vscode-extension/tsconfig.json, website/tsconfig.json)
54.7/55Tamaños de archivo manejables — 16/2566 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languageHTML
largest_source_bytes677.463
source_files_sampled2566
oversized_source_files16

Interfaces legibles por máquina

100Excepcional
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto) — no aplicable a este tipo de software
20/20Servidor MCP
40/40Ejemplos ejecutables — demos, examples
Datos de entrada utilizados
example_dirsdemos, examples
has_mcp_signalsí
api_schema_files—
interfaces_expected_of—
Excluidos de la puntuación (sin datos o no aplicable): Esquema de API (OpenAPI/GraphQL/proto). Los pesos restantes se han renormalizado.

Datos clave

10estrellas de GitHub
2contribuidores
4134commits en los últimos 12 meses
1días desde el último push
100versiones publicadas
1factor bus
6issues abiertas
npm, PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi download statistics for 'attune-ai' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • Could not fetch pypi package 'attune-redis' from its registry
  • Could not fetch npm package 'attune-dashboard' from its registry
  • pypi download figures for attune-ai carried forward from the previous scan (stats endpoint unavailable this scan)

Más detalle

Historial de estrellas y forks 0 ★ / 2 ⇿
0Estrellas
2Forks
91Versiones

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.

111222212026-022026-052026-08
Mayor 9Menor 47Parche 34
OpenSSF Scorecard 7.0 / 10
7.0agregado

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 · 2026-09-15 23:32 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-Tests25 out of 25 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 0/29 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
n/dDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
n/dFuzzinginternal error: internal error: Client.Search.Code: http.Get: Get "https://oss-fuzz-build-logs.storage.googleapis.com/status.json": dial tcp [2a00:1450:4001:c1f::cf]:443: connect: network is unreachable
10Licenselicense file detected
10Maintained30 commit(s) and 30 issue activity found in the last 90 days -- score normalized to 10
n/dPackagingpackaging workflow not detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
n/dToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 48
RegistroPaqueteRestricción de versiónManifiesto
PyPIattune-ai>=3.5.0attune_redis/pyproject.toml
PyPIagent-memory-client>=0.14.0attune_redis/pyproject.toml
PyPIredis>=5.0.0,<8.0.0attune_redis/pyproject.toml
PyPIpydantic>=2.4.0,<3.0.0pyproject.toml
PyPItyping-extensions>=4.0.0,<5.0.0pyproject.toml
PyPIpython-dotenv>=1.0.0,<2.0.0pyproject.toml
PyPIstructlog>=24.0.0,<27.0.0pyproject.toml
PyPIattune-forms>=0.17.0,<0.18pyproject.toml
PyPIjsonschema>=4.26.0,<5.0.0pyproject.toml
PyPIdefusedxml>=0.7.0,<1.0.0pyproject.toml
PyPIrich>=13.0.0,<16.0.0pyproject.toml
PyPItyper>=0.9.0,<1.0.0pyproject.toml
PyPIpyyaml>=6.0,<7.0pyproject.toml
PyPIanthropic>=0.40.0,<2.0.0pyproject.toml
PyPIclaude-agent-sdk>=0.2.152,<0.3.0pyproject.toml
PyPImcp==1.29.1pyproject.toml
PyPIpython-multipart>=0.0.26pyproject.toml
PyPIcryptography>=50.0.0pyproject.toml
PyPIlangsmith>=0.7.31,<2.0.0pyproject.toml
PyPIjinja2>=3.1.0,<4.0.0pyproject.toml
PyPIpython-frontmatter>=1.0.0,<2.0.0pyproject.toml
PyPIattune-rag>=1.2.0,<2.0pyproject.toml
PyPIattune-verify>=0.1.0,<1.0pyproject.toml
PyPItomli>=2.0.0pyproject.toml
PyPIagent-memory-client>=0.14.0,<0.15pyproject.toml
PyPIredis>=5.0.0,<9.0.0pyproject.toml
npm@mdx-js/loader^3.1.1website/package.json
npm@mdx-js/react^3.1.1website/package.json
npm@next/mdx^16.0.1website/package.json
npm@vercel/analytics^2.0.1website/package.json
npm@vercel/speed-insights^2.0.0website/package.json
npmbcryptjs^3.0.2website/package.json
npmgray-matter^4.0.3website/package.json
npmioredis^5.8.2website/package.json
npmnext^16.3.4website/package.json
npmnodemailer^9.1.1website/package.json
npmpg^8.16.3website/package.json
npmreact19.1.4website/package.json
npmreact-dom19.1.4website/package.json
npmreact-markdown^10.1.0website/package.json
npmreading-time^1.5.0website/package.json
npmreading-time-estimator^1.14.0website/package.json
npmrecharts^3.6.0website/package.json
npmrehype-highlight^7.0.2website/package.json
npmremark^15.0.1website/package.json
npmremark-gfm^4.0.1website/package.json
npmresend^6.18.1website/package.json
npmuuid^14.0.1website/package.json
Todas las dependencias 966

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 54 paquetes directos y 912 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
npm@mdx-js/loader3.1.1directa
npm@mdx-js/react3.1.1directa
npm@next/mdx16.0.1directa
npm@vercel/analytics2.0.1directa
npm@vercel/speed-insights2.0.0directa
npmbcryptjs3.0.2directa
npmgray-matter4.0.3directa
npmioredis5.8.2directa
npmnext16.3.4directa
npmnodemailer9.1.1directa
npmpg8.16.3directa
npmreact19.1.4directa
npmreact-dom19.1.4directa
npmreact-markdown10.1.0directa
npmreading-time1.5.0directa
npmreading-time-estimator1.14.0directa
npmrecharts3.6.0directa
npmrehype-highlight7.0.2directa
npmremark15.0.1directa
npmremark-gfm4.0.1directa
npmresend6.18.1directa
npmuuid14.0.1directa
PyPIagent-memory-client—directa
PyPIagent-memory-client0.14.0directa
PyPIanthropic0.125.0directa
PyPIattune-ai—directa
PyPIattune-ai16.4.0directa
PyPIattune-forms0.17.0directa
PyPIattune-rag1.2.0directa
PyPIattune-verify0.6.1directa
PyPIclaude-agent-sdk0.2.152directa
PyPIcryptography50.0.0directa
PyPIdefusedxml0.7.1directa
PyPIjinja23.1.6directa
PyPIjsonschema4.26.0directa
PyPIlangsmith0.10.2directa
PyPImcp1.29.1directa
PyPIpydantic—directa
PyPIpydantic2.13.4directa
PyPIpython-dotenv—directa
PyPIpython-dotenv1.2.2directa
PyPIpython-frontmatter1.3.0directa
PyPIpython-multipart0.0.32directa
PyPIpyyaml6.0.3directa
PyPIredis—directa
PyPIredis8.0.1directa
PyPIrich15.0.0directa
PyPIstructlog—directa
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Instalar pypi:attune-ai@16.4.0 arrastra 68 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.

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