Registro público
Informe de salud del softwareesquema 0.12.0 · métricas 1.13.0 · 2026-07-18 13:30 UTC

jaidedai / easyocr

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Python · C++Apache-2.0★ 29.775 estrellas⑂ 3586 forksdesde mar 2020Ver en GitHub ↗

jaidedai/easyocr tiene un índice de salud de 47 sobre 100, lo que lo sitúa en la banda En riesgo. Su puntuación más alta es Community & Adoption (76/100) y la más baja, Vitality (23/100). Se actualizó por última vez hace 225 días. Una sola persona concentra la mayor parte del trabajo reciente.

47
global / 100
En riesgo

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.

47
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

Jaided AIOrganización
234 seguidores1 repositorio públicodesde feb 2020

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
PyPIeasyocr1.7.2-33hace 662 díasocropticalcharacterrecognitiondeeplearningneuralnetwork

Métricas por categoría

Vitalidad

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

23Crítico · 22% del índice global
Cómo se puntúa
3.6/36Recencia de push — último push hace 225 días
0.7/36Cadencia de commits — 1/52 semanas con commits
2.7/18Volumen de commits — 1 commits en el último año
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Datos de entrada utilizados
commits_last_year1
human_commit_share
days_since_last_push225
active_weeks_last_year1
Cómo se puntúa
27/27Publica versiones — 23 versiones publicadas
7.2/36Recencia de las versiones — última versión hace 662 días
12.6/27Cadencia de publicación — una versión cada ~131,5 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count23
latest_release_tagv1.7.2
releases_from_tagsno
days_since_latest_release662
mean_days_between_releases131,5

Comunidad y Adopción

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

76Bueno · 18% del índice global
Cómo se puntúa
60/60Estrellas — 29.775 estrellas
25/25Forks — 3586 forks
14/15Observadores — 329 observadores
Datos de entrada utilizados
forks3586
stars29.775
watchers329
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (Apache-2.0)
0/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
0/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributingno
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno

Sostenibilidad y Gobernanza

¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?

60Moderado · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
9.8/22.5Distribución de commits — el principal contribuyente firma el 56% de los commits
13.5/13.5Amplitud de contribuyentes — 100 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations
Datos de entrada utilizados
bus_factor1
contributors_sampled100
top_contributor_share0,565
Cómo se puntúa
26.3/46.8Resolución de issues — 56% de issues cerradas
29.6/38.3Aceptación de PR — 177/229 PR decididos fusionados
9/15OpenSSF Scorecard: Code-Review — Found 15/22 approved changesets -- score normalized to 6
Datos de entrada utilizados
merged_prs177
open_issues475
closed_issues610
issue_closed_ratio0,562
closed_unmerged_prs52
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
17/25Alcance del propietario — 234 seguidores de JaidedAI
14.2/25Trayectoria — 1 repos públicos, cuenta de ~6 años
Datos de entrada utilizados
followers234
owner_typeOrganization
is_verified
owner_loginJaidedAI
public_repos1
account_age_days2335
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
14/35Recencia de publicación — última publicación hace 662 días
20/20Historial de versiones — 33 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packageseasyocr
ecosystemspypi
any_deprecatedno
min_days_since_publish662

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

44En 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
0/20OpenSSF Scorecard: CI-Tests — 0 out of 16 merged PRs checked by a CI test -- score normalized to 0
Datos de entrada utilizados
has_cino
has_tests
has_editorconfigno
has_linter_configno
has_precommit_configno
Cómo se puntúa
30/30README
0/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://www.jaided.ai
10/10Descripción del repositorio
10/10Topics — 15 topics
10/10Wiki
Datos de entrada utilizados
topicsocr, deep-learning, crnn, pytorch, lstm, machine-learning, scene-text, scene-text-recognition, optical-character-recognition, cnn, data-mining, image-processing, python, easyocr, information-retrieval
has_wiki
homepagehttps://www.jaided.ai
has_readme
has_docs_dirno
has_description

Seguridad

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

30En riesgo · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — 0 out of 16 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 15/22 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 9 contributing companies or organizations
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
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — sin datos
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — sin datos
0/7.5Vulnerabilities — 39 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3
Excluidos de la puntuación (sin datos o no aplicable): dangerous_workflow, packaging, token_permissions. 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.

30En riesgo · 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
0/18Arranque con un solo comando
22/22Pruebas automatizadas
0/11Configuración de lint / formato
0/11Verificación estática de tipos
10/10Entorno reproducible — Dockerfile
0/10Práctica demostrada con agentes — sin datos
0/8Mantenimiento automatizado — sin datos
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfiles
has_dockerfile
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes, Mantenimiento automatizado. Los pesos restantes se han renormalizado.
Cómo se puntúa
0/45Código verificable por tipos — Python sin configuración de verificación de tipos
54.4/55Tamaños de archivo manejables — 1/85 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes91.824
source_files_sampled85
oversized_source_files1
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — examples, notebooks
Datos de entrada utilizados
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files

Datos clave

29.775estrellas de GitHub
100contribuidores
1commits en los últimos 12 meses
225días desde el último push
23versiones publicadas
1factor bus
475issues abiertas
PyPIecosistemas de paquetes

Más detalle

OpenSSF Scorecard 3.0 / 10
3.0agregado

Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-07-18 13:29 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 16 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 15/22 approved changesets -- score normalized to 6
10Contributorsproject has 9 contributing companies or organizations
n/dDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/dPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
n/dToken-PermissionsNo tokens found
0Vulnerabilities39 existing vulnerabilities detected
Todas las dependencias 22

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 0 paquetes directos y 22 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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PyPIpyclipperindirecta
PyPIpython-bidiindirecta
PyPIpyyamlindirecta
PyPIpyyaml5.4.1indirecta
PyPIscikit-imageindirecta
PyPIscikit-image0.17.2indirecta
PyPIscipyindirecta
PyPIshapelyindirecta
PyPIshapely1.8.0indirecta
PyPItorchindirecta
PyPItorch1.13.1indirecta
PyPItorchvisionindirecta
PyPItorchvision0.10.0indirecta
PyPIwandb0.12.9indirecta
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        {
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                "details": [],
                "max_points": 24
              },
              {
                "key": "tests_present",
                "name": "Tests present",
                "detail": null,
                "points": 24,
                "status": "met",
                "details": [],
                "max_points": 24
              },
              {
                "key": "linter_config",
                "name": "Linter config",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 16
              },
              {
                "key": "pre_commit_hooks",
                "name": "Pre-commit hooks",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 9.6
              },
              {
                "key": "editorconfig",
                "name": ".editorconfig",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 6.4
              },
              {
                "key": "openssf_scorecard_ci_tests",
                "name": "OpenSSF Scorecard: CI-Tests",
                "detail": "0 out of 16 merged PRs checked by a CI test -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              }
            ]
          },
          {
            "key": "documentation",
            "band": "good",
            "name": "Documentation",
            "note": null,
            "notes": [],
            "value": 75,
            "inputs": {
              "topics": [
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                "pytorch",
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                "image-processing",
                "python",
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              "has_wiki": true,
              "homepage": "https://www.jaided.ai",
              "has_readme": true,
              "has_docs_dir": false,
              "has_description": true
            },
            "components": [
              {
                "key": "readme",
                "name": "README",
                "detail": null,
                "points": 30,
                "status": "met",
                "details": [],
                "max_points": 30
              },
              {
                "key": "documentation_directory",
                "name": "Documentation directory",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 25
              },
              {
                "key": "documentation_homepage_site",
                "name": "Documentation / homepage site",
                "detail": "https://www.jaided.ai",
                "points": 15,
                "status": "met",
                "details": [],
                "max_points": 15
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              {
                "key": "repository_description",
                "name": "Repository description",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "topics",
                "name": "Topics",
                "detail": "15 topics",
                "points": 10,
                "status": "met",
                "details": [
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                "max_points": 10
              },
              {
                "key": "wiki",
                "name": "Wiki",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
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            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
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        "weight": 0.16,
        "metrics": [
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            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
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            ],
            "value": 30,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 15,
              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 3,
              "scorecard_aggregate": 3
            },
            "components": [
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                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
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              {
                "key": "ci_tests",
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                "points": 0,
                "status": "missed",
                "details": [],
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              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 15/22 approved changesets -- score normalized to 6",
                "points": 4.5,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
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                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no workflows found",
                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
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                "detail": "update tool detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
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                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
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                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
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                ],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
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                "points": 0,
                "status": "missed",
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              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
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                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
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                ],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
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                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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            "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": {
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              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 4
            },
            "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
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            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 30,
        "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": [
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                    "code": "no_agent_instructions",
                    "params": {}
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                ],
                "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": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "at_risk",
            "name": "Verify loop (build / test / typecheck)",
            "note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
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            "value": 39,
            "inputs": {
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              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
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                "points": 0,
                "status": "missed",
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              },
              {
                "key": "automated_tests",
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                "points": 22,
                "status": "met",
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              },
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                "points": 0,
                "status": "missed",
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              },
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              },
              {
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                "detail": "Dockerfile",
                "points": 10,
                "status": "met",
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                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
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                "points": 0,
                "status": "excluded",
                "details": [
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                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no data",
                "points": 0,
                "status": "excluded",
                "details": [
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                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
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                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
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            "note": null,
            "notes": [],
            "value": 54,
            "inputs": {
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              "largest_source_bytes": 91824,
              "source_files_sampled": 85,
              "oversized_source_files": 1
            },
            "components": [
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                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
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                    "code": "no_typecheck_config_language",
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
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                "detail": "1/85 source files over 60KB",
                "points": 54.4,
                "status": "partial",
                "details": [
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                    "code": "oversized_source_files",
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                      "sampled": 85,
                      "oversized": 1
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                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
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            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
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              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples, notebooks",
                "points": 40,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
                      "files": "examples, notebooks"
                    }
                  }
                ],
                "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": [],
  "report_type": "repository",
  "generated_at": "2026-07-18T13:30:19.547249Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/j/jaidedai/easyocr.svg",
  "full_name": "jaidedai/easyocr",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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

Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.12.0 — metodología completa · wiki de métricas.

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