Registro público
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-28 14:38 UTC

python-coincidence / coincidence

Helper functions for pytest.

PythonMIT★ 3 estrellas⑂ 2 forksdesde ene 2021Ver en GitHub ↗

python-coincidence/coincidence tiene un índice de salud de 54 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (77/100) y la más baja, Community & Adoption (44/100). Se actualizó por última vez hace 19 días. Una sola persona concentra la mayor parte del trabajo reciente.

54
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.

54
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

CoincidenceOrganización
1 seguidor12 repositorios públicosdesde mar 2021

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
PyPIcoincidence0.6.618.49122hace 875 díaspytestregressiontestingunittestutilities

Métricas por categoría

Vitalidad

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

45En riesgo · 22% del índice global
Cómo se puntúa
28.8/36Recencia de push — último push hace 19 días
4.2/36Cadencia de commits — 6/52 semanas con commits
9/18Volumen de commits — 9 commits en el último año
1/10OpenSSF Scorecard: Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
Datos de entrada utilizados
commits_last_year9
human_commit_share0,51
days_since_last_push19
active_weeks_last_year6
Cómo se puntúa
27/27Publica versiones — 22 versiones publicadas
0/36Recencia de las versiones — última versión hace 875 días
19.8/27Cadencia de publicación — una versión cada ~111 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count22
latest_release_tagv0.6.6
releases_from_tagsno
days_since_latest_release875
mean_days_between_releases111

Comunidad y Adopción

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

44En riesgo · 18% del índice global
Cómo se puntúa
4.9/60Estrellas — 3 estrellas
0/25Forks — 2 forks
0/15Observadores — 1 observadores
Datos de entrada utilizados
forks2
stars3
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (MIT)
18/18Guía 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_contributing
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno
Cómo se puntúa
56.9/80Descargas mensuales — 18.491 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagescoincidence
dependents
ecosystemspypi
total_downloads
monthly_downloads18.491
Excluidos de la puntuación (sin datos o no aplicable): Dependientes en el registro. Los pesos restantes se han renormalizado.

Sostenibilidad y Gobernanza

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

46En riesgo · 24% del índice global
Cómo se puntúa
9/54Factor bus — la mitad de los commits recae en 1 contribuyente(s)
0/22.5Distribución de commits — el principal contribuyente firma el 100% de los commits
1.4/13.5Amplitud de contribuyentes — 1 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 8 contributing companies or organizations
Datos de entrada utilizados
bus_factor1
contributors_sampled1
top_contributor_share1
Cómo se puntúa
23.4/46.8Resolución de issues — 50% de issues cerradas
31.2/38.3Aceptación de PR — 80/98 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — Found 0/7 approved changesets -- score normalized to 0
Datos de entrada utilizados
merged_prs80
open_issues2
closed_issues2
issue_closed_ratio0,5
closed_unmerged_prs18
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
2.2/25Alcance del propietario — 1 seguidores de python-coincidence
18.8/25Trayectoria — 12 repos públicos, cuenta de ~5 años
Datos de entrada utilizados
followers1
owner_typeOrganization
is_verified
owner_loginpython-coincidence
public_repos12
account_age_days1953
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
4/35Recencia de publicación — última publicación hace 875 días
20/20Historial de versiones — 22 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagescoincidence
ecosystemspypi
any_deprecatedno
min_days_since_publish875

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

77Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 8 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — .pylintrc, tox.ini
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
4/20OpenSSF Scorecard: CI-Tests — 6 out of 23 merged PRs checked by a CI test -- score normalized to 2
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_config
Cómo se puntúa
30/30README
0/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://coincidence.readthedocs.io/en/latest
10/10Descripción del repositorio
10/10Topics — 6 topics
10/10Wiki
Datos de entrada utilizados
topicspytest, python, regression, testing, unittest, utilities
has_wiki
homepagehttps://coincidence.readthedocs.io/en/latest
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?

59Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — sin datos
0.5/2.5CI-Tests — 6 out of 23 merged PRs checked by a CI test -- score normalized to 2
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/7 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 8 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
0.8/7.5Maintained — 2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
5/5Packaging — packaging workflow detected
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.
4.5/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6.8/7.5Vulnerabilities — 1 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate4,9
Excluidos de la puntuación (sin datos o no aplicable): branch_protection. Los pesos restantes se han renormalizado.
Cómo se puntúa
35/35Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido
25/25Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages11
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:coincidence@0.6.6 —lo que arrastra la instalación del paquete publicado—: 11 paquetes. No se analiza la alcanzabilidad.

Preparación para IA

¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Es una insignia independiente y experimental — peso 0,0, de modo que se presenta por separado y no afecta a la puntuación de salud global.

46En 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 — 0 de 51 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
18/18Arranque con un solo comando — justfile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — .pylintrc, tox.ini
11/11Verificación estática de tipos — coincidence/py.typed
0/10Entorno reproducible
0/10Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
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_dockerfileno
typed_languageno
bootstrap_filesjustfile
has_devcontainerno
has_linter_config
typecheck_configscoincidence/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (coincidence/py.typed)
55/55Tamaños de archivo manejables — 0/17 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes12.594
source_files_sampled17
oversized_source_files0

Datos clave

3estrellas de GitHub
1contribuidores
9commits en los últimos 12 meses
19días desde el último push
22versiones publicadas
1factor bus
2issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

Más detalle

Historial de estrellas y forks 0 ★ / 2 ⇿
0Estrellas
2Forks
1Versiones

Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.

111222212023-112024-102025-08
Mayor 0Menor 0Parche 1

Cada punto abarca 2 días.

OpenSSF Scorecard 4.9 / 10
4.9agregado

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 · 2026-07-28 14:37 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
2CI-Tests6 out of 23 merged PRs checked by a CI test -- score normalized to 2
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/7 approved changesets -- score normalized to 0
10Contributorsproject has 8 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
1Maintained2 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 1
10Packagingpackaging workflow 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.
6Token-Permissionsdetected GitHub workflow tokens with excessive permissions
9Vulnerabilities1 existing vulnerabilities detected
Todas las dependencias 39

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 0 paquetes directos y 39 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIbackports-entry-points-selectableindirecta
PyPIcoverageindirecta
PyPIcoverage-pyver-pragmaindirecta
PyPIdefault-valuesindirecta
PyPIdocutilsindirecta
PyPIdomdf-python-toolsindirecta
PyPIdomdf-sphinx-themeindirecta
PyPIextras-requireindirecta
PyPIhtml-sectionindirecta
PyPIimportlib-metadataindirecta
PyPIiniconfigindirecta
PyPIpytestindirecta
PyPIpytest-covindirecta
PyPIpytest-randomlyindirecta
PyPIpytest-regressionsindirecta
PyPIpytest-timeoutindirecta
PyPIromanindirecta
PyPIseed-intersphinx-mappingindirecta
PyPIsetuptoolsindirecta
PyPIsphinxindirecta
PyPIsphinx-autofixtureindirecta
PyPIsphinx-copybuttonindirecta
PyPIsphinx-debuginfoindirecta
PyPIsphinx-faviconindirecta
PyPIsphinx-licenseinfoindirecta
PyPIsphinx-notfound-pageindirecta
PyPIsphinx-pyprojectindirecta
PyPIsphinx-toolboxindirecta
PyPIsphinxcontrib-applehelp1.0.4indirecta
PyPIsphinxcontrib-devhelp1.0.2indirecta
PyPIsphinxcontrib-htmlhelp2.0.1indirecta
PyPIsphinxcontrib-httpdomainindirecta
PyPIsphinxcontrib-jsmath1.0.1indirecta
PyPIsphinxcontrib-qthelp1.0.3indirecta
PyPIsphinxcontrib-serializinghtml1.1.5indirecta
PyPIsphinxemojiindirecta
PyPItoctree-plusindirecta
PyPItomlindirecta
PyPItyping-extensionsindirecta
Avisos de dependencias 0

Instalar pypi:coincidence@0.6.6 arrastra 11 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.

Ningún aviso conocido afecta a las dependencias evaluadas.

Un aviso significa que la versión registrada en el grafo de dependencias cae dentro del rango afectado de un aviso. No se analiza la alcanzabilidad, y el grafo incluye fijaciones de desarrollo y prueba: un hallazgo puede referirse al utillaje y no al software distribuido.

Informe JSON sin procesar legible por máquina
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                "key": "openssf_scorecard_contributors",
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                "key": "pr_acceptance",
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              },
              {
                "key": "dependency_update_tool",
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                "key": "fuzzing",
                "name": "Fuzzing",
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                "key": "license",
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              },
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                "key": "maintained",
                "name": "Maintained",
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                "key": "packaging",
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                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 4.5,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "1 existing vulnerabilities detected",
                "points": 6.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "dependency_advisories",
            "band": "excellent",
            "name": "Dependency advisories",
            "note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:coincidence@0.6.6 runtime dependency closure — what installing the published package pulls in — 11 packages. Reachability is not analyzed.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "no_advisories_left_outstanding"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              },
              {
                "code": "advisories_scope_published",
                "params": {
                  "package": "pypi:coincidence@0.6.6",
                  "assessed": 11
                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "source": "osv",
              "advisories": 0,
              "affected_packages": 0,
              "assessed_packages": 11,
              "unassessed_packages": 0,
              "affected_by_severity": "none",
              "direct_affected_packages": 0
            },
            "components": [
              {
                "key": "direct_dependencies_free_of_known_advisories",
                "name": "Direct dependencies free of known advisories",
                "detail": "no direct dependency carries a known advisory",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "no_direct_advisories",
                    "params": {}
                  }
                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
              },
              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
                "detail": "no advisory carries a publication date",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "advisories_no_publication_date",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "malicious_dependencies",
            "band": "excellent",
            "name": "Malicious dependencies",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "source": "osv",
              "meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
              "packages": [],
              "red_flag": false,
              "assessed_packages": 11,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
            },
            "components": [
              {
                "key": "no_dependency_reported_as_a_malicious_package",
                "name": "No dependency reported as a malicious package",
                "detail": "no dependency is reported as a malicious package",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "no_malicious_dependencies",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 9
            },
            "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": "at_risk",
        "name": "AI Readiness",
        "value": 46,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "critical",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 1,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0,
              "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": "0 of 51 human commits state their intent (structured subject or explanatory body)",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 0,
                      "sampled": 51
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 67,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [],
              "has_dockerfile": false,
              "typed_language": false,
              "bootstrap_files": [
                "justfile"
              ],
              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [
                "coincidence/py.typed"
              ],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": "justfile",
                "points": 18,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "justfile"
                    }
                  }
                ],
                "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": ".pylintrc, tox.ini",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": ".pylintrc, tox.ini"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "coincidence/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "coincidence/py.typed"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no agent-authored commits among the last 100",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_authored_commits",
                    "params": {
                      "sampled": 100
                    }
                  }
                ],
                "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": "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": 12594,
              "source_files_sampled": 17,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (coincidence/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "coincidence/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/17 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 17,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-28T14:38:04.149718Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/python-coincidence/coincidence.svg",
  "full_name": "python-coincidence/coincidence",
  "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 v0.27.0 — metodología completa · wiki de métricas.

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