Registro público
Informe de salud del softwareesquema 0.12.0 · métricas 1.13.0 · 2026-07-18 06:11 UTC

QCHackers / tqec

Design automation software tools for Topological Quantum Error Correction

PythonApache-2.0★ 376 estrellas⑂ 119 forksdesde oct 2023Ver en GitHub ↗

QCHackers/tqec tiene un índice de salud de 79 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Engineering Quality (92/100) y la más baja, AI Readiness (54/100). Se actualizó por última vez hoy. 3 personas concentran la mayor parte del trabajo reciente.

79
global / 100
Bueno

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.

79
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

TQECOrganización
90 seguidores10 repositorios públicosdesde nov 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 publicaciónEtiquetas
PyPItqecapunta a otro repositorio; no se puntúa0.2.042283hace 114 díastopological-quantum-error-correctionqec

Métricas por categoría

Vitalidad

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

89Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
33.9/36Cadencia de commits — 49/52 semanas con commits
18/18Volumen de commits — 221 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year221
human_commit_share
days_since_last_push0
active_weeks_last_year49
Cómo se puntúa
27/27Publica versiones — 2 versiones publicadas
27/36Recencia de las versiones — última versión hace 114 días
12.6/27Cadencia de publicación — una versión cada ~133,1 días
8/10OpenSSF Scorecard: Signed-Releases — 2 out of the last 2 releases have a total of 2 signed artifacts.
Datos de entrada utilizados
releases_count2
latest_release_tagv0.2.0
releases_from_tagsno
days_since_latest_release114
mean_days_between_releases133,1

Comunidad y Adopción

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

71Bueno · 18% del índice global
Cómo se puntúa
41.8/60Estrellas — 376 estrellas
17.3/25Forks — 119 forks
6.2/15Observadores — 14 observadores
Datos de entrada utilizados
forks119
stars376
watchers14
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)
18/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_templateno
has_code_of_conductno
has_pull_request_template

Sostenibilidad y Gobernanza

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

73Bueno · 24% del índice global
Cómo se puntúa
36/54Factor bus — la mitad de los commits recae en 3 contribuyente(s)
16.2/22.5Distribución de commits — el principal contribuyente firma el 28% de los commits
13.5/13.5Amplitud de contribuyentes — 32 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations
Datos de entrada utilizados
bus_factor3
contributors_sampled32
top_contributor_share0,28
Cómo se puntúa
39.6/46.8Resolución de issues — 85% de issues cerradas
32.9/38.3Aceptación de PR — 494/575 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs494
open_issues61
closed_issues338
issue_closed_ratio0,847
closed_unmerged_prs81
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
14.1/25Alcance del propietario — 90 seguidores de tqec
11/25Trayectoria — 10 repos públicos, cuenta de ~1 años
Datos de entrada utilizados
followers90
owner_typeOrganization
is_verified
owner_logintqec
public_repos10
account_age_days616

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

92Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 6 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_config

Documentación

90Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://tqec.github.io/tqec/
10/10Descripción del repositorio
10/10Topics — 3 topics
0/10Wiki
Datos de entrada utilizados
topicsquantum-error-correction, surface-code, quantum-computing
has_wikino
homepagehttps://tqec.github.io/tqec/
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?

66Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 9 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 2 issue activity found in the last 90 days -- score normalized to 10
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
6/7.5Signed-Releases — 2 out of the last 2 releases have a total of 2 signed artifacts.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6,6
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, packaging. 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.

54Moderado · 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 — docs/Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato
11/11Verificación estática de tipos — src/tqec/py.typed
10/10Entorno reproducible — lockfile
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
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_config
typecheck_configssrc/tqec/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. Los pesos restantes se han renormalizado.
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (src/tqec/py.typed)
54.6/55Tamaños de archivo manejables — 2/276 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes104.008
source_files_sampled276
oversized_source_files2
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — notebooks
Datos de entrada utilizados
example_dirsnotebooks
has_mcp_signalno
api_schema_files

Datos clave

376estrellas de GitHub
32contribuidores
221commits en los últimos 12 meses
0días desde el último push
2versiones publicadas
3factor bus
61issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • pypi package 'tqec' points at a different repository (https://github.com/tqec/tqec); excluded from ecosystem scoring

Más detalle

OpenSSF Scorecard 6.6 / 10
6.6agregado

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 06:11 UTC

10Binary-Artifactsno binaries found in the repo
n/dBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 9 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 2 issue activity found in the last 90 days -- score normalized to 10
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
8Signed-Releases2 out of the last 2 releases have a total of 2 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Dependencias directas 20
RegistroPaqueteRestricción de versiónManifiesto
PyPImatplotlib>=3.9pyproject.toml
PyPInetworkx>=3.0pyproject.toml
PyPInumpy>=1.22pyproject.toml
PyPInumpy>=1.24pyproject.toml
PyPInumpy>=1.26pyproject.toml
PyPInumpy>=2.1pyproject.toml
PyPIplatformdirs>=4.0pyproject.toml
PyPIpycollada>=0.8pyproject.toml
PyPIpymatching>=2.3.1pyproject.toml
PyPIpyzx>=0.9.0pyproject.toml
PyPIscipy>=1.15pyproject.toml
PyPIsemver>=3.0.0pyproject.toml
PyPIsinter>=1.14pyproject.toml
PyPIsphinx-design>=0.6.1pyproject.toml
PyPIstim>=1.14pyproject.toml
PyPIstim>=1.15pyproject.toml
PyPIsvg-py>=1.10.0pyproject.toml
PyPItqecd>=0.2.1pyproject.toml
PyPItyping-extensions>=4.2pyproject.toml
PyPItyping-extensions>=4.12pyproject.toml
Todas las dependencias 203

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 22 paquetes directos y 181 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
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PyPImatplotlib3.11.0directa
PyPInetworkx3.4.2directa
PyPInetworkx3.6.1directa
PyPInumpy2.2.6directa
PyPInumpy2.4.6directa
PyPInumpy2.5.1directa
PyPIplatformdirs4.10.0directa
PyPIpycollada0.9.3directa
PyPIpymatching2.4.0directa
PyPIpyzx0.10.4directa
PyPIscipy1.15.3directa
PyPIscipy1.17.1directa
PyPIscipy1.18.0directa
PyPIsemver3.0.4directa
PyPIsinter1.16.0directa
PyPIsphinx-design0.6.1directa
PyPIsphinx-design0.7.0directa
PyPIstim1.16.0directa
PyPIsvg-py1.10.0directa
PyPItqecd0.2.1directa
PyPItyping-extensions4.16.0directa
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PyPIanyio4.14.2indirecta
PyPIappnope0.1.4indirecta
PyPIargon2-cffi25.1.0indirecta
PyPIargon2-cffi-bindings25.1.0indirecta
PyPIarrow1.4.0indirecta
PyPIasttokens3.0.2indirecta
PyPIasync-lru2.3.0indirecta
PyPIattrs26.1.0indirecta
PyPIbabel2.18.0indirecta
PyPIbeautifulsoup44.15.0indirecta
PyPIbleach6.4.0indirecta
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PyPIcffi2.1.0indirecta
PyPIcfgv3.5.0indirecta
PyPIcharset-normalizer3.4.9indirecta
PyPIclick8.4.2indirecta
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PyPIcomm0.2.3indirecta
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PyPIexecuting2.2.1indirecta
PyPIfastjsonschema2.21.2indirecta
PyPIfilelock3.29.7indirecta
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PyPIfqdn1.5.1indirecta
PyPIgprof2dot2025.4.14indirecta
PyPIh110.16.0indirecta
PyPIhttpcore1.0.9indirecta
PyPIhttpx0.28.1indirecta
PyPIidentify2.6.19indirecta
PyPIidna3.18indirecta
PyPIimagesize2.0.0indirecta
PyPIiniconfig2.3.0indirecta
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PyPIjupyter-lsp2.3.1indirecta
PyPIjupyter-server2.20.0indirecta
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PyPIjupyterlab-pygments0.3.0indirecta
PyPIjupyterlab-server2.28.0indirecta
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PyPIwidgetsnbextension4.0.15indirecta
Informe JSON sin procesar legible por máquina
{
  "data": {
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        "quantum-error-correction",
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      "pushed_at": "2026-07-18T04:29:32Z",
      "created_at": "2023-10-19T16:33:34Z",
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "2 out of the last 2 releases have a total of 2 signed artifacts.",
                "points": 6,
                "status": "partial",
                "details": [],
                "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": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "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": {
              "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": 6
            },
            "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": 54,
        "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. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "demonstrated_agent_practice",
                    "automated_maintenance"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 88,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "docs/Makefile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "src/tqec/py.typed"
              ],
              "agent_commit_share": null,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": null
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "docs/Makefile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "docs/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": 11,
                "status": "met",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "src/tqec/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "src/tqec/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": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "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": 104008,
              "source_files_sampled": 276,
              "oversized_source_files": 2
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (src/tqec/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "src/tqec/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "2/276 source files over 60KB",
                "points": 54.6,
                "status": "partial",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 276,
                      "oversized": 2
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "notebooks"
              ],
              "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": "notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "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": [
    "pypi package 'tqec' points at a different repository (https://github.com/tqec/tqec); excluded from ecosystem scoring"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-18T06:11:36.492254Z",
  "schema_version": "0.12.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/q/QCHackers/tqec.svg",
  "full_name": "QCHackers/tqec",
  "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.