Informe de auditoría del skill
linkedin-humanizer Informe de auditoría.
Scrub AI tells from any text draft OR audit a finished post against the 2026 algorithm heuristic checklist. Tier-based rewriter (forensic / strict / aesthetic / all) plus `--mode audit` for detection-only pass-fail review covering length, hook, CTA, format penalties, AI vocab. Also `--mode profile` builds a reusable Voice and Brand Profile from a few of the user''s real posts, so every writing skill drafts in their voice. Sub-tools: emoji-pattern detector, multi-detector spread tester (GPTZero, Originality.ai, ZeroGPT, Sapling, Copyleaks), rule explainer. Triggers on "humanize", "de-AI", "review this draft", "audit before posting", "is this ready", "build my voice profile", "learn my voice".
Trust Score de OpenAgentSkill
Trust Score de OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopción en GitHub
Aprobado86
1.3K estrellas de GitHub
Actividad de stars/forks
Info77
1.3K estrellas y 204 forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado88
1 meses desde el último push
Claridad de licencia
Aprobado86
MIT
Completitud de README/SKILL.md
Info76
Los metadatos públicos necesitan más contexto de README/SKILL.md
Riesgo de dependencias/runtime
Advertencia54
command execution surface, credential or environment access
Disponibilidad de instalación
Aprobado92
npx skills add sergebulaev/linkedin-skills --skill linkedin-humanizer
Seguridad del comando de instalación
Aprobado92
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
Fallido36
secrets or environment access, shell or command execution
Evidencia del repositorio
Aprobado86
https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-humanizer
Estado de revisión
Info66
Hay datos de revisión por IA disponibles
Resultados comprobados por Agent
Info54
Aún no hay datos de resultados del Agent
Comprobaciones
Revisión de instalación y adopción
Ruta de instalación
92
npx skills add sergebulaev/linkedin-skills --skill linkedin-humanizer
Repositorio
88
https://github.com/sergebulaev/linkedin-skills/tree/main/.codex-marketplace/linkedin-skills/skills/linkedin-humanizer
Licencia
86
MIT
Mantenimiento
88
1 meses desde el último push
Revisión por IA
55
The skill references sub-skills and reference files (e.g., sub-skills/rules-explainer.md, references/scrub-rules.md) that are not fully included in the provided excerpt, but they are present in the repository and appear to be part of the complete skill package.
Completitud de README/SKILL.md
84
Usable description available
Riesgo de dependencias
54
command execution surface, credential or environment access
Seguridad del comando de instalación
92
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
36
secrets or environment access, shell or command execution
Actividad de stars/forks
77
1.3K estrellas y 204 forks; la actividad de issues no está disponible en los metadatos actuales
Adopción
88
1.3K estrellas de GitHub
Advertencias
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The skill references sub-skills and reference files (e.g., sub-skills/rules-explainer.md, references/scrub-rules.md) that are not fully included in the provided excerpt, but they are present in the repository and appear to be part of the complete skill package.
- The skill mentions optional external API calls (e.g., APIFY_TOKEN for profile mode, AI detectors) which could send user content to third-party services. This is a potential privacy consideration, though it is clearly described and opt-in.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Método
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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