Registro público
Informe de salud del softwareesquema 0.12.0 · métricas 1.13.0 · 2026-07-17 16:46 UTC

phenobarbital / ai-parrot

Parrot is a new library to work with chatbots and agents with a very simple API

PythonMIT★ 27 estrellas⑂ 10 forksdesde ago 2024Ver en GitHub ↗

phenobarbital/ai-parrot tiene un índice de salud de 63 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Vitality (100/100) y la más baja, Community & Adoption (41/100). Se actualizó por última vez hoy. Una sola persona concentra la mayor parte del trabajo reciente.

63
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.

63
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

phenobarbitalCuenta personal
124 seguidores77 repositorios públicosdesde oct 2009DEVEL

Este repositorio pertenece a una cuenta personal. Un proyecto con un único propietario conlleva más riesgo de continuidad que uno respaldado por una organización.

Métricas por categoría

Vitalidad

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

100Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
36/36Cadencia de commits — 52/52 semanas con commits
18/18Volumen de commits — 8451 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year8451
human_commit_share
days_since_last_push0
active_weeks_last_year52
Cómo se puntúa
27/27Publica versiones — 100 versiones publicadas
36/36Recencia de las versiones — última versión hace 0 días
27/27Cadencia de publicación — una versión cada ~4,1 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count100
latest_release_tag0.25.20
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases4,1
Excluidos de la puntuación (sin datos o no aplicable): OpenSSF Scorecard: Signed-Releases. Los pesos restantes se han renormalizado.

Comunidad y Adopción

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

41En riesgo · 18% del índice global
Cómo se puntúa
23/60Estrellas — 27 estrellas
8/25Forks — 10 forks
2.7/15Observadores — 4 observadores
Datos de entrada utilizados
forks10
stars27
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
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?

43En riesgo · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
1.8/22.5Distribución de commits — el principal contribuyente firma el 92% de los commits
13.5/13.5Amplitud de contribuyentes — 11 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations
Datos de entrada utilizados
bus_factor1
contributors_sampled11
top_contributor_share0,922
Cómo se puntúa
0/46.8Resolución de issues — 0% de issues cerradas
33.2/38.3Aceptación de PR — 887/1021 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — Found 0/2 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs887
open_issues1
closed_issues0
issue_closed_ratio0
closed_unmerged_prs134
Cómo se puntúa
10/30Respaldo de la propiedad — cuenta personal (usuario)
0/20Dominio verificado — no aplicable a cuentas de usuario
15.1/25Alcance del propietario — 124 seguidores de phenobarbital
25/25Trayectoria — 77 repos públicos, cuenta de ~16 años
Datos de entrada utilizados
followers124
owner_typeUser
is_verified
owner_loginphenobarbital
public_repos77
account_age_days6120
Excluidos de la puntuación (sin datos o no aplicable): Dominio verificado. Los pesos restantes se han renormalizado.

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

74Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 5 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — .flake8, .pylintrc, tox.ini
0/9.6Hooks de pre-commit
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — 0 out of 2 merged PRs checked by a CI test -- score normalized to 0
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_configno

Documentación

90Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://phenobarbital.github.io/ai-parrot/
10/10Descripción del repositorio
10/10Topics — 7 topics
0/10Wiki
Datos de entrada utilizados
topicsartificial-intelligence, claude-ai, google-genai, groq-ai, openai, orchestration, xai-api
has_wikino
homepagehttps://phenobarbital.github.io/ai-parrot/
has_readme
has_docs_dir
has_description

Seguridad

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

55Moderado · 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 2 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
0/7.5Code-Review — Found 0/2 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 7 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Licencia — license file detected
7.5/7.5Maintained — 30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — sin datos
3.5/5SAST — SAST tool detected but not run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — sin datos
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 42 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5,5
Excluidos de la puntuación (sin datos o no aplicable): pinned_dependencies, 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.

88Excelente · 0% del índice global
Cómo se puntúa
45/45Instrucciones para agentes — AGENTS.md, CLAUDE.md, docs/agent.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, docs/agent.md
agent_instruction_max_bytes13.619
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
18/18Arranque con un solo comando — Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — .flake8, .pylintrc, tox.ini
11/11Verificación estática de tipos — mypy.ini, packages/ai-parrot-loaders/src/parrot_loaders/py.typed, packages/ai-parrot-pipelines/src/parrot_pipelines/py.typed, packages/ai-parrot-tools/src/parrot_tools/py.typed, packages/ai-parrot/src/parrot/py.typed, packages/parrot-formdesigner/src/parrot_formdesigner/py.typed
10/10Entorno reproducible — Dockerfile, lockfile
0/10Práctica demostrada con agentes — sin datos
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
0/10OpenSSF Scorecard: Pinned-Dependencies — sin datos
Datos de entrada utilizados
has_nixno
has_tests
lockfilesCargo.lock, go.sum
has_dockerfile
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_config
typecheck_configsmypy.ini, packages/ai-parrot-loaders/src/parrot_loaders/py.typed, packages/ai-parrot-pipelines/src/parrot_pipelines/py.typed, packages/ai-parrot-tools/src/parrot_tools/py.typed, packages/ai-parrot/src/parrot/py.typed, packages/parrot-formdesigner/src/parrot_formdesigner/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes, 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 (mypy.ini, packages/ai-parrot-loaders/src/parrot_loaders/py.typed, packages/ai-parrot-pipelines/src/parrot_pipelines/py.typed, packages/ai-parrot-tools/src/parrot_tools/py.typed, packages/ai-parrot/src/parrot/py.typed, packages/parrot-formdesigner/src/parrot_formdesigner/py.typed)
54.3/55Tamaños de archivo manejables — 50/3942 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes1.030.855
source_files_sampled3942
oversized_source_files50
Cómo se puntúa
40/40Esquema de API (OpenAPI/GraphQL/proto) — packages/ai-parrot-server/src/parrot/mcp/transports/mcp.proto, packages/ai-parrot/src/parrot/core/events/bus/ingress/proto/events.proto
20/20Servidor MCP
40/40Ejemplos ejecutables — examples
Datos de entrada utilizados
example_dirsexamples
has_mcp_signal
api_schema_filespackages/ai-parrot-server/src/parrot/mcp/transports/mcp.proto, packages/ai-parrot/src/parrot/core/events/bus/ingress/proto/events.proto

Datos clave

27estrellas de GitHub
11contribuidores
8451commits en los últimos 12 meses
0días desde el último push
100versiones publicadas
1factor bus
1issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Could not fetch pypi package 'ai-parrot-workspace' from its registry

Más detalle

OpenSSF Scorecard 5.5 / 10
5.5agregado

Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-07-17 16:46 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 2 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/2 approved changesets -- score normalized to 0
10Contributorsproject has 7 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
n/dPinned-Dependenciesinternal error: internal error: invalid Dockerfile
7SASTSAST tool detected but not run on all commits
10Security-Policysecurity policy file detected
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities42 existing vulnerabilities detected
Dependencias directas 9
RegistroPaqueteRestricción de versiónManifiesto
PyPIai-parrotpyproject.toml
PyPIai-parrot-toolspyproject.toml
PyPIai-parrot-loaderspyproject.toml
PyPIai-parrot-embeddingspyproject.toml
PyPIai-parrot-visualizationspyproject.toml
PyPIai-parrot-pipelinespyproject.toml
PyPIai-parrot-integrationspyproject.toml
PyPIai-parrot-serverpyproject.toml
PyPIai-parrot-advisorspyproject.toml
Todas las dependencias 349

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 1 paquetes directos y 348 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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crates.iolibc0.2.177indirecta
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crates.ioonce_cell1.21.3indirecta
crates.ioportable-atomic1.11.1indirecta
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                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
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                "status": "partial",
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              },
              {
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                "status": "met",
                "details": [],
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              },
              {
                "key": "signed_releases",
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                "points": 0,
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                "details": [
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                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "42 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "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": {
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              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 6
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
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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",
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        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
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            "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": [
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
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            "inputs": {
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                "detail": "AGENTS.md, CLAUDE.md, docs/agent.md",
                "points": 45,
                "status": "met",
                "details": [
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                    "code": "file_list",
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                ],
                "max_points": 45
              },
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                "key": "machine_readable_docs_llms_txt",
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                "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": {}
                  }
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                "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, OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 96,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "Cargo.lock",
                "go.sum"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
                "Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
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                "packages/ai-parrot-tools/src/parrot_tools/py.typed",
                "packages/ai-parrot/src/parrot/py.typed",
                "packages/parrot-formdesigner/src/parrot_formdesigner/py.typed"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "Makefile",
                "points": 18,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
                      "files": "Makefile"
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                ],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
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                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
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                "detail": ".flake8, .pylintrc, tox.ini",
                "points": 11,
                "status": "met",
                "details": [
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                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
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                "points": 11,
                "status": "met",
                "details": [
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                    "code": "file_list",
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                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
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                      "files": "Dockerfile, 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": "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",
                "detail": "internal error: internal error: invalid Dockerfile",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 10
              }
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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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              "largest_source_bytes": 1030855,
              "source_files_sampled": 3942,
              "oversized_source_files": 50
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (mypy.ini, packages/ai-parrot-loaders/src/parrot_loaders/py.typed, packages/ai-parrot-pipelines/src/parrot_pipelines/py.typed, packages/ai-parrot-tools/src/parrot_tools/py.typed, packages/ai-parrot/src/parrot/py.typed, packages/parrot-formdesigner/src/parrot_formdesigner/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
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                    "code": "typecheck_config_language",
                    "params": {
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                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "50/3942 source files over 60KB",
                "points": 54.3,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
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                      "sampled": 3942,
                      "oversized": 50
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                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "excellent",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
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              "has_mcp_signal": true,
              "api_schema_files": [
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                "points": 40,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
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                ],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 20,
                "status": "met",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
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                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "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": [
    "Could not fetch pypi package 'ai-parrot-workspace' from its registry"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-17T16:46:40.147720Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/phenobarbital/ai-parrot.svg",
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  "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 v0.12.0 — metodología completa · wiki de métricas.

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