Registro públicoBueno
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-29 15:55 UTC
triton-inference-server / model_analyzer
Triton Model Analyzer is a CLI tool to help with better understanding of the compute and memory requirements of the Triton Inference Server models.
triton-inference-server/model_analyzer tiene un índice de salud de 77 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Sustainability & Governance (87/100) y la más baja, AI Readiness (44/100). Se actualizó por última vez hace 5 días. 3 personas concentran la mayor parte del trabajo reciente.
77
global / 100Índice 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.
77
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)
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
Triton Inference ServerOrganización
2032 seguidores36 repositorios públicosdesde jul 2020
Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.
Ecosistemas de paquetes
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación | Etiquetas |
|---|---|---|---|---|---|---|
| PyPI | triton-model-analyzer | 1.56.0 | 10.607 | 58 | hace 0 días | tritontensorrtinferenceserverserviceanalyzernvidia |
Métricas por categoría
Vitalidad
¿Está vivo el proyecto: se escribe código y se publican versiones?
81
Actividad de desarrollo
74Bueno
Cómo se puntúa
| 36/36 | Recencia de push — último push hace 5 días |
| 18/36 | Cadencia de commits — 26/52 semanas con commits |
| 14.9/18 | Volumen de commits — 45 commits en el último año |
| 5/10 | OpenSSF Scorecard: Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5 |
Datos de entrada utilizados
| commits_last_year | 45 |
| human_commit_share | 1 |
| days_since_last_push | 5 |
| active_weeks_last_year | 26 |
Disciplina de publicación
92Excelente
Cómo se puntúa
| 27/27 | Publica versiones — 34 versiones publicadas |
| 36/36 | Recencia de las versiones — última versión hace 32 días |
| 19.8/27 | Cadencia de publicación — una versión cada ~64,1 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
Datos de entrada utilizados
| releases_count | 34 |
| latest_release_tag | v1.55.0 |
| releases_from_tags | no |
| days_since_latest_release | 32 |
| mean_days_between_releases | 64,1 |
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?
68
Popularidad y adopción
66Moderado
Cómo se puntúa
| 44.1/60 | Estrellas — 523 estrellas |
| 16.2/25 | Forks — 88 forks |
| 5.3/15 | Observadores — 10 observadores |
Datos de entrada utilizados
| forks | 88 |
| stars | 523 |
| watchers | 10 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Salud de la comunidad
70Bueno
Cómo se puntúa
| 22.5/22.5 | README |
| 22.5/22.5 | Licencia — licencia reconocida (Apache-2.0) |
| 18/18 | Guía CONTRIBUTING |
| 0/13.5 | Código de conducta |
| 0/7.2 | Plantilla de issues |
| 0/6.3 | Plantilla de PR |
Datos de entrada utilizados
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | no |
Adopción en el ecosistema (descargas)
67Moderado
Cómo se puntúa
| 53.7/80 | Descargas mensuales — 10.607 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
Datos de entrada utilizados
| packages | triton-model-analyzer |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 10.607 |
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?
87
Cómo se puntúa
| 36/54 | Factor bus — la mitad de los commits recae en 3 contribuyente(s) |
| 17.2/22.5 | Distribución de commits — el principal contribuyente firma el 24% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 25 contribuyentes |
| 10/10 | OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations |
Datos de entrada utilizados
| bus_factor | 3 |
| contributors_sampled | 25 |
| top_contributor_share | 0,236 |
Capacidad de respuesta a issues y PR
97Excelente
Cómo se puntúa
| 46/46.8 | Resolución de issues — 98% de issues cerradas |
| 35.8/38.3 | Aceptación de PR — 799/853 PR decididos fusionados |
| 15/15 | OpenSSF Scorecard: Code-Review — all changesets reviewed |
Datos de entrada utilizados
| merged_prs | 799 |
| open_issues | 3 |
| closed_issues | 171 |
| issue_closed_ratio | 0,983 |
| closed_unmerged_prs | 54 |
Propiedad y custodia
77Bueno
Cómo se puntúa
| 30/30 | Respaldo de la propiedad — propiedad de una organización |
| 0/20 | Dominio verificado |
| 23.8/25 | Alcance del propietario — 2032 seguidores de triton-inference-server |
| 23.4/25 | Trayectoria — 36 repos públicos, cuenta de ~6 años |
Datos de entrada utilizados
| followers | 2032 |
| owner_type | Organization |
| is_verified | — |
| owner_login | triton-inference-server |
| public_repos | 36 |
| account_age_days | 2210 |
Mantenimiento de paquetes
100Excelente
Cómo se puntúa
| 25/25 | Publicado y resoluble — 1 paquete(s) en pypi |
| 35/35 | Recencia de publicación — última publicación hace 0 días |
| 20/20 | Historial de versiones — 58 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
Datos de entrada utilizados
| packages | triton-model-analyzer |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 0 |
Calidad de Ingeniería
¿Existen unas prácticas mínimas de ingeniería y documentación?
85
Prácticas de ingeniería
92Excelente
Cómo se puntúa
| 24/24 | Flujos de trabajo de CI — 3 flujo(s) de trabajo |
| 24/24 | Pruebas presentes |
| 16/16 | Configuración de linter |
| 9.6/9.6 | Hooks de pre-commit |
| 0/6.4 | .editorconfig |
| 18/20 | OpenSSF Scorecard: CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9 |
Datos de entrada utilizados
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | sí |
| has_precommit_config | sí |
Documentación
75Bueno
Cómo se puntúa
| 30/30 | README |
| 25/25 | Directorio de documentación |
| 0/15 | Sitio de documentación / página del proyecto |
| 10/10 | Descripción del repositorio |
| 10/10 | Topics — 4 topics |
| 0/10 | Wiki |
Datos de entrada utilizados
| topics | deep-learning, inference, gpu, performance-analysis |
| has_wiki | no |
| homepage | — |
| has_readme | sí |
| has_docs_dir | sí |
| has_description | sí |
Seguridad
¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?
57
Postura de seguridad
57Moderado
Cómo se puntúa
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 4.5/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 2.2/2.5 | CI-Tests — 29 out of 30 merged PRs checked by a CI test -- score normalized to 9 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 7.5/7.5 | Code-Review — all changesets reviewed |
| 2.5/2.5 | Contributors — project has 7 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Licencia — license file detected |
| 3.8/7.5 | Maintained — 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5 |
| 0/5 | Packaging — sin datos |
| 0.5/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1 |
| 4.5/5 | SAST — SAST tool detected but not run on all commits |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — sin datos |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Datos de entrada utilizados
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 5,7 |
Excluidos de la puntuación (sin datos o no aplicable): packaging, 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.
44
Contexto y guía para agentes
40En riesgo
Cómo se puntúa
| 0/45 | Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor |
| 0/15 | Documentación legible por máquinas (llms.txt) |
| 40/40 | Historial de commits legible — 97 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo) |
Datos de entrada utilizados
| has_llms_txt | no |
| legible_history_share | 0,97 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Cómo se puntúa
| 0/18 | Arranque con un solo comando |
| 22/22 | Pruebas automatizadas |
| 11/11 | Configuración de lint / formato |
| 0/11 | Verificación estática de tipos |
| 10/10 | Entorno reproducible — Dockerfile |
| 0/10 | Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100 |
| 0/8 | Mantenimiento automatizado — no se observan actualizaciones automáticas de dependencias |
| 1/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1 |
Datos de entrada utilizados
| has_nix | no |
| has_tests | sí |
| lockfiles | — |
| has_dockerfile | sí |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | sí |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Legibilidad del código para modelos
54Moderado
Cómo se puntúa
| 0/45 | Código verificable por tipos — Python sin configuración de verificación de tipos |
| 54.5/55 | Tamaños de archivo manejables — 3/347 archivos fuente de más de 60 KB |
Datos de entrada utilizados
| primary_language | Python |
| largest_source_bytes | 82.674 |
| source_files_sampled | 347 |
| oversized_source_files | 3 |
Interfaces legibles por máquina
40En riesgo
Cómo se puntúa
| 0/40 | Esquema de API (OpenAPI/GraphQL/proto) |
| 0/20 | Servidor MCP |
| 40/40 | Ejemplos ejecutables — examples |
Datos de entrada utilizados
| example_dirs | examples |
| has_mcp_signal | no |
| api_schema_files | — |
Datos clave
523estrellas de GitHub
25contribuidores
45commits en los últimos 12 meses
5días desde el último push
34versiones publicadas
3factor bus
3issues abiertas
PyPIecosistemas de paquetes
Advertencias de recopilación de datos
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
- deps.dev does not index pypi:triton-model-analyzer@1.56.0; advisories assessed against the repository dependency graph instead
Más detalle
Historial de estrellas y forks 0 ★ / 88 ⇿
0Estrellas
88Forks
34Versiones
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.
Mayor 0Menor 34Parche 0
Cada punto abarca 6 días.
OpenSSF Scorecard 5.7 / 10
5.7agregado
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 6 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 9 | CI-Tests | 29 out of 30 merged PRs checked by a CI test -- score normalized to 9 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 10 | Code-Review | all changesets reviewed |
| 10 | Contributors | project has 7 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 5 | Maintained | 6 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5 |
| n/d | Packaging | packaging workflow not detected |
| 1 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 1 |
| 9 | SAST | SAST tool detected but not run on all commits |
| 0 | Security-Policy | security policy file not detected |
| n/d | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Dependencias directas 18
| Registro | Paquete | Restricción de versión | Manifiesto |
|---|---|---|---|
| PyPI | cryptography | >=3.3.2 | pyproject.toml |
| PyPI | distro | >=1.5.0 | pyproject.toml |
| PyPI | docker | >=4.3.1 | pyproject.toml |
| PyPI | gevent | >=22.08.0 | pyproject.toml |
| PyPI | grpcio | >=1.81.1 | pyproject.toml |
| PyPI | httplib2 | >=0.19.0 | pyproject.toml |
| PyPI | importlib_metadata | >=7.1.0 | pyproject.toml |
| PyPI | matplotlib | >=3.3.4 | pyproject.toml |
| PyPI | numba | >=0.51.2 | pyproject.toml |
| PyPI | optuna | ==3.6.1 | pyproject.toml |
| PyPI | pdfkit | >=0.6.1 | pyproject.toml |
| PyPI | prometheus_client | >=0.9.0 | pyproject.toml |
| PyPI | protobuf | — | pyproject.toml |
| PyPI | psutil | >=5.8.0 | pyproject.toml |
| PyPI | pyyaml | >=5.3.1 | pyproject.toml |
| PyPI | requests | >=2.24.0 | pyproject.toml |
| PyPI | tritonclient | >=2.4.0 | pyproject.toml |
| PyPI | urllib3 | >=2.0.7 | pyproject.toml |
Todas las dependencias no recopilado
No fue posible recopilar el conjunto de dependencias resuelto para este informe: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Informe JSON sin procesar legible por máquina
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"body": "* Update README and versions for 1.40.0 / 24.05 (#872)\r\n\r\n* Update README and versions for 1.40.0 / 24.05 (#883)\r\n\r\n* Update README and versions for 1.40.0 / 24.05\r\n\r\n* Fix the versions\r\n\r\n---------\r\n\r\nCo-authored-by: Misha Chornyi <99709299+mc-nv@users.noreply.github.com>",
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"headline": "Update main post 24.05 release (#888)",
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"headline": "Run CPU-only unit tests automatically for pull requests (#873)",
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"headline": "Update Dockerfile configuartion. (#860)",
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"body": "* Updating documentation for LLM metric support\r\n\r\n* Rewriting LLM config search paragraph for clarity",
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"headline": "Adding LLM Metrics to MA documentation (#856)",
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"body": "* New Records for LLM metrics (#839)\r\n\r\n* Adding new LLM metrics\r\n\r\n* Adding base class for perf, inter_token, and time_to_first latency records\r\n\r\n* Add --llm-mode option (#842)\r\n\r\n* Adding CLI hook for LLM\r\n\r\n* Changing to use --model-type\r\n\r\n* Capture LLM metrics from genai-perf in MA (#844)\r\n\r\n*\n[…]\nperf CLI\r\n\r\n* Remove dead code\r\n\r\n* Removing genai_perf collateral\r\n\r\n* Fixing codeQL issue\r\n\r\n* Adding streaming to genai_perf_config\r\n\r\n---------\r\n\r\nCo-authored-by: root <root@braf-linux.nvidia.com>",
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"headline": "Merge LLM Metrics changes to main (#855)",
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"headline": "Update 'main' post-24.03 (#851)",
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"headline": "Remove early access note (#841)",
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"body": "* Update README and versions for 1.36.0 / 24.01 (#813)\r\n\r\n* Update README and versions for 1.36.0 / 24.01\r\n\r\n* Update redme\r\n\r\n* fix typoe\r\n\r\n* Update REAMDE.md post 24.01\r\n\r\n* Fix version",
"is_bot": false,
"headline": "Update README.md and versions post-24.01 (#822)",
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"headline": "Update QRCG to set concurrency for default config (#820)",
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"body": "* Revert \"Add MVP LLM support to MA (#783)\"\r\n\r\nThis reverts commit f15427ef86a68777a5d718af26d50e0b23907df2.\r\n\r\n* Fixing merge conficts",
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"headline": "Fix loading of composing models for ensembles (#810)",
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"headline": "Update 'main' to track development for 1.37.0 / 24.02 (#811)",
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"author_name": "Timothy Gerdes",
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"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
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"points": 0.5,
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},
{
"key": "sast",
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"points": 4.5,
"status": "partial",
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},
{
"key": "security_policy",
"name": "Security-Policy",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
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"points": 0,
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"details": [
{
"code": "no_data",
"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",
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"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": {}
}
],
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"inputs": {
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"red_flag": false,
"exposures": [],
"policy_countries": [
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"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 5
},
"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": 44,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "at_risk",
"name": "Agent context & guidance",
"note": null,
"notes": [],
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"inputs": {
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"legible_history_share": 0.97,
"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",
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"detail": "97 of 100 human commits state their intent (structured subject or explanatory body)",
"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
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"sampled": 100
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
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"note": null,
"notes": [],
"value": 44,
"inputs": {
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"has_tests": true,
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"toolchain_manifests": [],
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},
"components": [
{
"key": "one_command_bootstrap",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
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"detail": null,
"points": 22,
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},
{
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{
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{
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"details": [
{
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}
],
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},
{
"key": "demonstrated_agent_practice",
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"detail": "no agent-authored commits among the last 100",
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"details": [
{
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],
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},
{
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],
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},
{
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"detail": "dependency not pinned by hash detected -- score normalized to 1",
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"details": [],
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}
]
},
{
"key": "ai_code_legibility",
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"name": "Code legibility for models",
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"notes": [],
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"oversized_source_files": 3
},
"components": [
{
"key": "type_checkable_code",
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"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
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}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "3/347 source files over 60KB",
"points": 54.5,
"status": "partial",
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{
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],
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]
},
{
"key": "ai_interfaces",
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"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
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],
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"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "mcp_server",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
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},
{
"key": "runnable_examples",
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"detail": "examples",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
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}
}
],
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}
]
}
],
"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",
"GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository",
"deps.dev does not index pypi:triton-model-analyzer@1.56.0; advisories assessed against the repository dependency graph instead"
],
"report_type": "repository",
"generated_at": "2026-07-29T15:55:58.107249Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/t/triton-inference-server/model_analyzer.svg",
"full_name": "triton-inference-server/model_analyzer",
"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 v0.27.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.