Informe de auditoría del skill
autoskill Informe de auditoría.
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
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
Aprobado100
34K estrellas de GitHub
Actividad de stars/forks
Aprobado97
34K estrellas y 3.3K forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado100
2 días desde el último push
Claridad de licencia
Aprobado86
MIT license
Completitud de README/SKILL.md
Aprobado86
Los metadatos incluyen suficiente contexto de uso y flujo de trabajo
Riesgo de dependencias/runtime
Advertencia46
command execution surface, credential or environment access
Disponibilidad de instalación
Aprobado92
npx skills add K-Dense-AI/scientific-agent-skills --skill autoskill
Seguridad del comando de instalación
Aprobado92
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
Fallido22
secrets or environment access, shell or command execution
Evidencia del repositorio
Aprobado86
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
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 K-Dense-AI/scientific-agent-skills --skill autoskill
Repositorio
88
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/autoskill
Licencia
86
MIT license
Mantenimiento
100
2 días desde el último push
Revisión por IA
55
The skill depends on the screenpipe daemon and a SCREENPIPE_TOKEN; if the daemon is not running or the token is invalid, the skill will fail. Documentation covers this, but a more explicit error-handling section in SKILL.md could help.
Completitud de README/SKILL.md
86
Usable description available
Riesgo de dependencias
46
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
22
secrets or environment access, shell or command execution
Actividad de stars/forks
97
34K estrellas y 3.3K forks; la actividad de issues no está disponible en los metadatos actuales
Adopción
88
34K estrellas de GitHub
Advertencias
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- The skill depends on the screenpipe daemon and a SCREENPIPE_TOKEN; if the daemon is not running or the token is invalid, the skill will fail. Documentation covers this, but a more explicit error-handling section in SKILL.md could help.
- Cloud backends (Claude/Foundry) are optional but require the user to supply API keys; the skill does not perform additional runtime validation of the endpoint beyond the cleartext check, so a misconfigured (but HTTPS) remote endpoint could receive data. This is acceptable given the user explicitly configures it, but the documentation could emphasise the privacy implications more strongly.
- 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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