Rapport d’audit du skill
power-analysis Rapport d’audit.
Use when the user is planning a two-arm comparison (an A/B test, a simple RCT, a behavioral study, or a two-model/two-config evaluation) and needs to size it and preregister it before collecting data — finding the per-group sample size that hits target statistical power for the smallest effect worth detecting, auditing the design against a validity checklist, and locking it in a preregistration. Only for a single two-arm comparison with one primary outcome. Not for factorial, repeated-measures, clustered/multilevel, time-series, adaptive, or survival designs; not for analyzing data already collected; not for choosing the outcome or manipulation from domain knowledge.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adoption GitHub
Info62
163 stars GitHub
Activité stars/forks
Avertissement57
163 stars et 19 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Info76
4 mois depuis le dernier push
Clarté de licence
Validé86
MIT
Complétude README/SKILL.md
Validé86
Les métadonnées incluent suffisamment de contexte d’usage et de workflow
Risque dépendances/runtime
Validé90
Aucun indice majeur de risque de dépendance dans les métadonnées publiques
Disponibilité de l’installation
Validé92
npx skills add gaasher/Agent-Loop-Skills --skill power-analysis
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Validé86
Accès au système de fichiers ou aux documents
Preuve du dépôt
Validé86
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/power-analysis
État de revue
Info66
Données de revue IA disponibles
Résultats prouvés par Agent
Info54
Pas encore de données de résultats Agent
Vérifications
Revue d’installation et d’adoption
Chemin d’installation
92
npx skills add gaasher/Agent-Loop-Skills --skill power-analysis
Dépôt
88
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/power-analysis
Licence
86
MIT
Maintenance
76
4 mois depuis le dernier push
Revue IA
55
The power simulation uses a normal approximation (z-test) which is slightly optimistic for very small sample sizes (<20 per group); this is documented but could mislead users if they ignore the caveat.
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
90
Aucun indice majeur de risque de dépendance dans les métadonnées publiques
Sécurité de la commande d’installation
92
Chemin d’installation standard de package ou runtime
Surface de permissions
86
Accès au système de fichiers ou aux documents
Activité stars/forks
57
163 stars et 19 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
68
163 stars GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Avertissements
- Financial research output is not financial advice; require human review before any live investment decision
- The power simulation uses a normal approximation (z-test) which is slightly optimistic for very small sample sizes (<20 per group); this is documented but could mislead users if they ignore the caveat.
- The skill is narrowly scoped to two-arm comparisons with continuous or binary outcomes; users with other designs must be careful not to misuse it.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Stars/forks activity: 163 stars, 19 forks; issue activity unavailable in current metadata
Méthode
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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