Registro público
Informe de salud del softwareesquema 0.16.0 · métricas 1.13.0 · 2026-07-21 02:32 UTC

deepset-ai / haystack

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

PythonApache-2.0★ 25.959 estrellas⑂ 2941 forksdesde nov 2019Ver en GitHub ↗
#nlp#question-answering#pytorch#semantic-search#information-retrieval#summarization#transformers#machine-learning#ai#python#large-language-models#generative-ai#llm#rag#retrieval-augmented-generation#agents#agent#gemini#gpt-4#orchestration

deepset-ai/haystack tiene un índice de salud de 93 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Vitality (100/100) y la más baja, AI Readiness (72/100). Se actualizó por última vez hoy. 7 personas concentran la mayor parte del trabajo reciente.

93
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.

93
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

deepsetOrganización
1367 seguidores74 repositorios públicosdesde jun 2019

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
PyPIhaystack-ai3.0.01.022.672166hace 0 díasbertqaquestion-answeringreaderretrieveralbertlanguage-modelmrcrobertasearchsemantic-searchsquadtransfer-learningtransformer

Métricas por categoría

Vitalidad

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

100Excelente · 22% del índice global

Actividad de desarrollo

100Excelente
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 — 1620 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_year1620
human_commit_share—
days_since_last_push0
active_weeks_last_year52

Disciplina de publicación

100Excelente
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 ~5,2 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count100
latest_release_tagv3.0.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases5,2
Excluidos de la puntuación (sin datos o no aplicable): OpenSSF Scorecard: Signed-Releases. Los pesos restantes se han renormalizado.

Comunidad y Adopción

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

96Excelente · 18% del índice global

Popularidad y adopción

97Excelente
Cómo se puntúa
60/60Estrellas — 25.959 estrellas
25/25Forks — 2941 forks
12.2/15Observadores — 160 observadores
Datos de entrada utilizados
forks2941
stars25.959
watchers160
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
has_contributingsí
has_issue_templateno
has_code_of_conductsí
has_pull_request_templatesí

Adopción en el ecosistema (descargas)

100Excelente
Cómo se puntúa
80/80Descargas mensuales — 1.022.672 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packageshaystack-ai
dependents—
ecosystemspypi
total_downloads—
monthly_downloads1.022.672
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?

92Excelente · 24% del índice global

Resiliencia de mantenedores (factor bus)

95Excelente
Cómo se puntúa
51.3/54Factor bus — la mitad de los commits recae en 7 contribuyente(s)
20/22.5Distribución de commits — el principal contribuyente firma el 11% de los commits
13.5/13.5Amplitud de contribuyentes — 100 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 12 contributing companies or organizations
Datos de entrada utilizados
bus_factor7
contributors_sampled100
top_contributor_share0,112

Capacidad de respuesta a issues y PR

94Excelente
Cómo se puntúa
46/46.8Resolución de issues — 98% de issues cerradas
33.4/38.3Aceptación de PR — 5694/6519 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs5694
open_issues74
closed_issues4335
issue_closed_ratio0,983
closed_unmerged_prs825

Propiedad y custodia

78Bueno
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
22.5/25Alcance del propietario — 1367 seguidores de deepset-ai
25/25Trayectoria — 74 repos públicos, cuenta de ~7 años
Datos de entrada utilizados
followers1367
owner_typeOrganization
is_verified—
owner_logindeepset-ai
public_repos74
account_age_days2593

Mantenimiento de paquetes

100Excelente
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 — 166 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packageshaystack-ai
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

82Bueno · 20% del índice global

Prácticas de ingeniería

94Excelente
Cómo se puntúa
24/24Flujos de trabajo de CI — 33 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_cisí
has_testssí
has_editorconfigno
has_linter_configsí
has_precommit_configsí

Documentación

65Moderado
Cómo se puntúa
30/30README
0/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://haystack.deepset.ai
10/10Descripción del repositorio
10/10Topics — 20 topics
0/10Wiki
Datos de entrada utilizados
topicsnlp, question-answering, pytorch, semantic-search, information-retrieval, summarization, transformers, machine-learning, ai, python, large-language-models, generative-ai, llm, rag, retrieval-augmented-generation, agents, agent, gemini, gpt-4, orchestration
has_wikino
homepagehttps://haystack.deepset.ai
has_readmesí
has_docs_dirno
has_descriptionsí

Seguridad

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

94Excelente · 16% del índice global

Postura de seguridad

94Excelente
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
6/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
1.2/2.5CII-Best-Practices — badge detected: Passing
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 12 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
5/5Fuzzing — project is 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
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
4/5SAST — SAST tool detected but not run on all commits
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
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate9,4
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.

72Bueno · 0% del índice global

Contexto y guía para agentes

75Bueno
Cómo se puntúa
45/45Instrucciones para agentes — AGENTS.md, 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_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes1480
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.

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

71Bueno
Cómo se puntúa
0/18Arranque con un solo comando
22/22Pruebas automatizadas
11/11Configuración de lint / formato
11/11Verificación estática de tipos — docs-website/api/tsconfig.json, haystack/py.typed
10/10Entorno reproducible — Dockerfile
0/10Práctica demostrada con agentes — sin datos
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Datos de entrada utilizados
has_nixno
has_testssí
lockfiles—
has_dockerfilesí
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configsí
typecheck_configsdocs-website/api/tsconfig.json, haystack/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.

Legibilidad del código para modelos

81Bueno
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (docs-website/api/tsconfig.json, haystack/py.typed)
54.2/55Tamaños de archivo manejables — 8/549 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes249.780
source_files_sampled549
oversized_source_files8

Interfaces legibles por máquina

60Moderado
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
20/20Servidor MCP
40/40Ejemplos ejecutables — examples, samples
Datos de entrada utilizados
example_dirsexamples, samples
has_mcp_signalsí
api_schema_files—

Datos clave

25.959estrellas de GitHub
100contribuidores
1620commits en los últimos 12 meses
0días desde el último push
100versiones publicadas
7factor bus
74issues abiertas
npm, PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • deps.dev does not index pypi:haystack-ai@3.0.0; advisories assessed against the repository dependency graph instead
  • No resolved dependencies carried a version and a supported ecosystem

Más detalle

OpenSSF Scorecard 9.4 / 10
9.4agregado

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 · 2026-07-21 02:31 UTC

10Binary-Artifactsno binaries found in the repo
8Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
5CII-Best-Practicesbadge detected: Passing
10Code-Reviewall changesets reviewed
10Contributorsproject has 12 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
10Fuzzingproject is fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
8SASTSAST tool detected but not run on all commits
10Security-Policysecurity policy file detected
n/dSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 35
RegistroPaqueteRestricción de versiónManifiesto
npm@docusaurus/core^3.10.0docs-website/package.json
npm@docusaurus/faster^3.10.0docs-website/package.json
npm@docusaurus/plugin-content-docs^3.10.0docs-website/package.json
npm@docusaurus/plugin-ideal-image^3.10.0docs-website/package.json
npm@docusaurus/plugin-client-redirects^3.10.0docs-website/package.json
npm@docusaurus/preset-classic^3.10.0docs-website/package.json
npm@mdx-js/react^3.0.0docs-website/package.json
npm@types/turndown^5.0.6docs-website/package.json
npm@vercel/node^5.5.6docs-website/package.json
npmclsx^2.0.0docs-website/package.json
npmdocusaurus-plugin-generate-llms-txt^0.0.1docs-website/package.json
npmprism-react-renderer^2.3.0docs-website/package.json
npmreact^19.0.0docs-website/package.json
npmreact-dom^19.0.0docs-website/package.json
npmsharp^0.35.0docs-website/package.json
npmturndown^7.2.2docs-website/package.json
npmvercel^56.1.0docs-website/package.json
PyPItqdm—pyproject.toml
PyPItenacity!=8.4.0pyproject.toml
PyPIlazy-imports—pyproject.toml
PyPIopenai>=1.99.2pyproject.toml
PyPIpydantic—pyproject.toml
PyPIJinja2—pyproject.toml
PyPIMarkupSafe—pyproject.toml
PyPIposthog!=3.12.0pyproject.toml
PyPIpyyaml—pyproject.toml
PyPImore-itertools—pyproject.toml
PyPInetworkx—pyproject.toml
PyPItyping_extensions>=4.7pyproject.toml
PyPIhttpx—pyproject.toml
PyPInumpy—pyproject.toml
PyPIpython-dateutil—pyproject.toml
PyPIjsonschema—pyproject.toml
PyPIdocstring-parser—pyproject.toml
PyPIfiletype—pyproject.toml
Todas las dependencias 24

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 21 paquetes directos y 3 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
npm@docusaurus/core^3.10.0directa
npm@docusaurus/faster^3.10.0directa
npm@docusaurus/plugin-client-redirects^3.10.0directa
npm@docusaurus/plugin-content-docs^3.10.0directa
npm@docusaurus/plugin-ideal-image^3.10.0directa
npm@docusaurus/preset-classic^3.10.0directa
npm@mdx-js/react^3.0.0directa
npm@types/turndown^5.0.6directa
npm@vercel/node^5.5.6directa
npmclsx^2.0.0directa
npmdocusaurus-plugin-generate-llms-txt^0.0.1directa
npmprism-react-renderer^2.3.0directa
npmreact^19.0.0directa
npmreact-dom^19.0.0directa
npmsharp^0.35.0directa
npmturndown^7.2.2directa
npmvercel^56.1.0directa
PyPIopenai—directa
PyPIposthog—directa
PyPItenacity—directa
PyPItyping-extensions—directa
npm@docusaurus/module-type-aliases^3.10.0indirecta
npm@docusaurus/types^3.10.0indirecta
PyPIhatchling—indirecta
Avisos de dependencias sin evaluar

El cotejo de avisos no pudo ejecutarse para este informe: No resolved dependencies carried a version and a supported ecosystem

Informe JSON sin procesar legible por máquina
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                "key": "owner_reach",
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                "key": "fuzzing",
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                "key": "security_policy",
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                "key": "vulnerabilities",
                "name": "Vulnerabilities",
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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": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 14
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "good",
        "name": "AI Readiness",
        "value": 72,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "good",
            "name": "Agent context & guidance",
            "note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "legible_commit_history"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 75,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "agent_instruction_files": [
                "AGENTS.md",
                "CLAUDE.md"
              ],
              "agent_instruction_max_bytes": 1480
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "AGENTS.md, CLAUDE.md",
                "points": 45,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "AGENTS.md, CLAUDE.md"
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                  }
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                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
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                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "good",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice"
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 71,
            "inputs": {
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              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
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                "haystack/py.typed"
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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": 0,
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                "details": [],
                "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": null,
                "points": 11,
                "status": "met",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
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                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs-website/api/tsconfig.json, haystack/py.typed"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile",
                "points": 10,
                "status": "met",
                "details": [
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                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "dependency automation configured, none observed in the sampled commits",
                "points": 5,
                "status": "partial",
                "details": [
                  {
                    "code": "dependency_bot_config_only",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
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                "status": "partial",
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              }
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          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 81,
            "inputs": {
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              "source_files_sampled": 549,
              "oversized_source_files": 8
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (docs-website/api/tsconfig.json, haystack/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
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                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
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                "points": 54.2,
                "status": "partial",
                "details": [
                  {
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            "key": "ai_interfaces",
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            "name": "Machine-readable interfaces",
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            "notes": [],
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            "inputs": {
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              "api_schema_files": []
            },
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                "key": "api_schema_openapi_graphql_proto",
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                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
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                "detail": null,
                "points": 20,
                "status": "met",
                "details": [],
                "max_points": 20
              },
              {
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                "detail": "examples, samples",
                "points": 40,
                "status": "met",
                "details": [
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                    "params": {
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                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "deps.dev does not index pypi:haystack-ai@3.0.0; advisories assessed against the repository dependency graph instead",
    "No resolved dependencies carried a version and a supported ecosystem"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-21T02:32:10.344140Z",
  "schema_version": "0.16.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/deepset-ai/haystack.svg",
  "full_name": "deepset-ai/haystack",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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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 v0.16.0 — metodología completa · wiki de métricas.

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