Informe de auditoría del skill
earnings-trade-analyzer Informe de auditoría.
Analyze recent post-earnings stocks using a 5-factor scoring system (Gap Size, Pre-Earnings Trend, Volume Trend, MA200 Position, MA50 Position). Scores each stock 0-100 and assigns A/B/C/D grades. Use when user asks about earnings trade analysis, post-earnings momentum screening, earnings gap scoring, or finding best recent earnings reactions.
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
Info62
127 estrellas de GitHub
Actividad de stars/forks
Info68
127 estrellas y 963 forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado100
30 días desde el último push
Claridad de licencia
Aprobado86
MIT
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 BaggaT236/AI-Trading-Skills --skill earnings-trade-analyzer
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/BaggaT236/AI-Trading-Skills/tree/main/skills/earnings-trade-analyzer
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 BaggaT236/AI-Trading-Skills --skill earnings-trade-analyzer
Repositorio
88
https://github.com/BaggaT236/AI-Trading-Skills/tree/main/skills/earnings-trade-analyzer
Licencia
86
MIT
Mantenimiento
100
30 días desde el último push
Revisión por IA
55
No critical security issues found. The skill uses an external API key (FMP_API_KEY) but does not expose it insecurely; it is passed via environment variable or CLI argument.
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
68
127 estrellas y 963 forks; la actividad de issues no está disponible en los metadatos actuales
Adopción
68
127 estrellas de GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Advertencias
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- No critical security issues found. The skill uses an external API key (FMP_API_KEY) but does not expose it insecurely; it is passed via environment variable or CLI argument.
- The skill relies on an external service (Financial Modeling Prep) which may have rate limits, but the documentation clearly states prerequisites and fallback procedures.
- Financial research output is not financial advice; require human review before any live investment decision.
- 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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