Registro público
Informe de salud del softwareesquema 0.17.0 · métricas 1.13.0 · 2026-07-21 04:14 UTC

tavily-ai / langchain-tavily

PythonMIT★ 25 estrellas⑂ 17 forksdesde mar 2025Ver en GitHub ↗

tavily-ai/langchain-tavily tiene un índice de salud de 55 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Security (78/100) y la más baja, Engineering Quality (36/100). Se actualizó por última vez hace 13 días. 3 personas concentran la mayor parte del trabajo reciente.

55
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.

55
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

Tavily AIOrganización
898 seguidores37 repositorios públicosdesde may 2024

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
PyPIlangchain-tavily0.2.18-21hace 95 días

Métricas por categoría

Vitalidad

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

44En riesgo · 22% del índice global
Cómo se puntúa
28.8/36Recencia de push — último push hace 13 días
16.6/36Cadencia de commits — 24/52 semanas con commits
17.5/18Volumen de commits — 87 commits en el último año
9/10OpenSSF Scorecard: Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
Datos de entrada utilizados
commits_last_year87
human_commit_share
days_since_last_push13
active_weeks_last_year24
Cómo se puntúa
0/27Publica versiones — sin versiones publicadas
0/36Recencia de las versiones — sin versiones
0/27Cadencia de publicación — sin versiones
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count0
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?

40En riesgo · 18% del índice global
Cómo se puntúa
22.4/60Estrellas — 25 estrellas
10/25Forks — 17 forks
0/15Observadores — 0 observadores
Datos de entrada utilizados
forks17
stars25
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonbelow_threshold
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (MIT)
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?

77Bueno · 24% del índice global
Cómo se puntúa
36/54Factor bus — la mitad de los commits recae en 3 contribuyente(s)
15.5/22.5Distribución de commits — el principal contribuyente firma el 31% de los commits
13.5/13.5Amplitud de contribuyentes — 11 contribuyentes
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Datos de entrada utilizados
bus_factor3
contributors_sampled11
top_contributor_share0,309
Cómo se puntúa
37.4/46.8Resolución de issues — 80% de issues cerradas
28.6/38.3Aceptación de PR — 53/71 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs53
open_issues2
closed_issues8
issue_closed_ratio0,8
closed_unmerged_prs18
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
21.2/25Alcance del propietario — 898 seguidores de tavily-ai
15.8/25Trayectoria — 37 repos públicos, cuenta de ~2 años
Datos de entrada utilizados
followers898
owner_typeOrganization
is_verified
owner_logintavily-ai
public_repos37
account_age_days793
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 95 días
20/20Historial de versiones — 21 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packageslangchain-tavily
ecosystemspypi
any_deprecatedno
min_days_since_publish95

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

36En riesgo · 20% del índice global
Cómo se puntúa
0/24Flujos de trabajo de CI
24/24Pruebas presentes
0/16Configuración de linter
0/9.6Hooks de pre-commit
0/6.4.editorconfig
10/20OpenSSF Scorecard: CI-Tests — 8 out of 15 merged PRs checked by a CI test -- score normalized to 5
Datos de entrada utilizados
has_cino
has_tests
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentación

40En riesgo
Cómo se puntúa
30/30README
0/25Directorio de documentación
0/15Sitio de documentación / página del proyecto
0/10Descripción del repositorio
0/10Topics
10/10Wiki
Datos de entrada utilizados
topics
has_wiki
homepage
has_readme
has_docs_dirno
has_descriptionno

Seguridad

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

78Bueno · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
4.5/7.5Branch-Protection — branch protection is not maximal on development and all release branches
1.2/2.5CI-Tests — 8 out of 15 merged PRs checked by a CI test -- score normalized to 5
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
0/10Dangerous-Workflow — sin datos
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Licencia — license file detected
6.8/7.5Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
0/5Packaging — sin datos
0/5Pinned-Dependencies — sin datos
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — sin datos
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_aggregate7,2
Excluidos de la puntuación (sin datos o no aplicable): dangerous_workflow, packaging, pinned_dependencies, signed_releases, token_permissions. Los pesos restantes se han renormalizado.
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_packages44
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:langchain-tavily@0.2.18 —lo que arrastra la instalación del paquete publicado—: 44 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? 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.

55Moderado · 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)
0/40Historial de commits legible — sin datos
Datos de entrada utilizados
has_llms_txtno
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
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
0/11Configuración de lint / formato
11/11Verificación estática de tipos — langchain_tavily/py.typed
10/10Entorno reproducible — lockfile
0/10Práctica demostrada con agentes — sin datos
0/8Mantenimiento automatizado — sin datos
0/10OpenSSF Scorecard: Pinned-Dependencies — sin datos
Datos de entrada utilizados
has_nixno
has_tests
lockfilespoetry.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configslangchain_tavily/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes, Mantenimiento automatizado, OpenSSF Scorecard: Pinned-Dependencies. Los pesos restantes se han renormalizado.
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (langchain_tavily/py.typed)
55/55Tamaños de archivo manejables — 0/23 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes30.150
source_files_sampled23
oversized_source_files0

Datos clave

25estrellas de GitHub
11contribuidores
87commits en los últimos 12 meses
13días desde el último push
0versiones publicadas
3factor bus
2issues abiertas
PyPIecosistemas de paquetes

Más detalle

Historial de estrellas y forks 25 ★ / 0 ⇿
25Estrellas

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.

05101520252522025-042025-112026-06

Cada punto abarca 2 días.

OpenSSF Scorecard 7.2 / 10
7.2agregado

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 04:14 UTC

10Binary-Artifactsno binaries found in the repo
6Branch-Protectionbranch protection is not maximal on development and all release branches
5CI-Tests8 out of 15 merged PRs checked by a CI test -- score normalized to 5
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
n/dDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
9Maintained11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9
n/dPackagingpackaging workflow not detected
n/dPinned-Dependenciesno dependencies found
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/dSigned-Releasesno releases found
n/dToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 4
RegistroPaqueteRestricción de versiónManifiesto
PyPIlangchain-core==1.4.6pyproject.toml
PyPIlangchain==1.3.9pyproject.toml
PyPIaiohttp^3.11.14pyproject.toml
PyPIrequests^2.32.3pyproject.toml
Todas las dependencias 74

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 4 paquetes directos y 70 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIaiohttp3.14.1directa
PyPIlangchain1.3.9directa
PyPIlangchain-core1.4.6directa
PyPIrequests2.33.0directa
PyPIaiohappyeyeballs2.6.1indirecta
PyPIaiosignal1.4.0indirecta
PyPIannotated-types0.7.0indirecta
PyPIanyio4.9.0indirecta
PyPIasync-timeout4.0.3indirecta
PyPIattrs25.3.0indirecta
PyPIcertifi2025.4.26indirecta
PyPIcffi1.17.1indirecta
PyPIcharset-normalizer3.4.1indirecta
PyPIcodespell2.4.1indirecta
PyPIcolorama0.4.6indirecta
PyPIexceptiongroup1.2.2indirecta
PyPIfrozenlist1.6.0indirecta
PyPIh110.16.0indirecta
PyPIhttpcore1.0.9indirecta
PyPIhttpx0.28.1indirecta
PyPIidna3.17indirecta
PyPIiniconfig2.1.0indirecta
PyPIjsonpatch1.33indirecta
PyPIjsonpointer3.0.0indirecta
PyPIlangchain-protocol0.0.15indirecta
PyPIlangchain-tests1.1.6indirecta
PyPIlanggraph1.2.4indirecta
PyPIlanggraph-checkpoint4.1.1indirecta
PyPIlanggraph-prebuilt1.1.0indirecta
PyPIlanggraph-sdk0.4.2indirecta
PyPIlangsmith0.8.18indirecta
PyPImarkdown-it-py4.0.0indirecta
PyPImdurl0.1.2indirecta
PyPImultidict6.4.3indirecta
PyPImypy1.15.0indirecta
PyPImypy-extensions1.1.0indirecta
PyPInumpy2.2.5indirecta
PyPIorjson3.11.6indirecta
PyPIormsgpack1.12.2indirecta
PyPIpackaging24.2indirecta
PyPIpluggy1.5.0indirecta
PyPIpropcache0.3.1indirecta
PyPIpy-cpuinfo9.0.0indirecta
PyPIpycparser2.22indirecta
PyPIpydantic2.11.3indirecta
PyPIpydantic-core2.33.1indirecta
PyPIpygments2.20.0indirecta
PyPIpytest9.0.3indirecta
PyPIpytest-asyncio0.23.3indirecta
PyPIpytest-benchmark5.0.1indirecta
PyPIpytest-codspeed4.1.0indirecta
PyPIpytest-recording0.13.4indirecta
PyPIpytest-socket0.7.0indirecta
PyPIpytest-watcher0.3.5indirecta
PyPIpyyaml6.0.2indirecta
PyPIrequests-toolbelt1.0.0indirecta
PyPIrich14.1.0indirecta
PyPIruff0.5.0indirecta
PyPIsniffio1.3.1indirecta
PyPIsyrupy5.1.0indirecta
PyPItenacity9.1.2indirecta
PyPItomli2.2.1indirecta
PyPItypes-requests2.32.0.20250328indirecta
PyPItyping-extensions4.13.2indirecta
PyPItyping-inspection0.4.0indirecta
PyPIurllib32.7.0indirecta
PyPIuuid-utils0.14.0indirecta
PyPIvcrpy8.2.1indirecta
PyPIwatchdog6.0.0indirecta
PyPIwebsockets15.0.1indirecta
PyPIwrapt1.17.3indirecta
PyPIxxhash3.6.0indirecta
PyPIyarl1.20.0indirecta
PyPIzstandard0.23.0indirecta
Avisos de dependencias 0

Instalar pypi:langchain-tavily@0.2.18 arrastra 44 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias 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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            ]
          },
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              },
              {
                "code": "advisories_scope_published",
                "params": {
                  "package": "pypi:langchain-tavily@0.2.18",
                  "assessed": 44
                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "source": "osv",
              "advisories": 0,
              "affected_packages": 0,
              "assessed_packages": 44,
              "unassessed_packages": 0,
              "affected_by_severity": "none",
              "direct_affected_packages": 0
            },
            "components": [
              {
                "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": [
                  {
                    "code": "no_direct_advisories",
                    "params": {}
                  }
                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
              },
              {
                "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": {}
                  }
                ],
                "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": 44,
              "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": 3
            },
            "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": 55,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "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": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": null,
              "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": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "excellent",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance, OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance",
                    "openssf_scorecard_pinned_dependencies"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 85,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "poetry.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": false,
              "typecheck_configs": [
                "langchain_tavily/py.typed"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "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": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "langchain_tavily/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "langchain_tavily/py.typed"
                    }
                  }
                ],
                "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 data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "no dependencies found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "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": 30150,
              "source_files_sampled": 23,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (langchain_tavily/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "langchain_tavily/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/23 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 23,
                      "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": [],
  "report_type": "repository",
  "generated_at": "2026-07-21T04:14:52.686616Z",
  "schema_version": "0.17.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/t/tavily-ai/langchain-tavily.svg",
  "full_name": "tavily-ai/langchain-tavily",
  "license_state": "standard",
  "license_spdx": "MIT"
}

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 v0.17.0 — metodología completa · wiki de métricas.

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