Rapport d’audit du skill
david-silver Rapport d’audit.
Applies the reasoning of David Silver, lead researcher on AlphaGo and AlphaZero at DeepMind, to problems of AI design, reinforcement learning, and open-ended discovery. Use this skill whenever you are designing AI systems, evaluating learning algorithms, balancing exploration vs. exploitation, choosing research problems, or discussing how to break past human performance ceilings. Reach for this whenever the user asks about self-play, Monte-Carlo Tree Search, tabula rasa learning, AGI, or moving from human-curated data to autonomous experience. It helps shift the focus from hardcoding human knowledge to building systems that learn for themselves.
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
122 stars GitHub
Activité stars/forks
Avertissement57
122 stars et 18 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Validé88
2 mois depuis le dernier push
Clarté de licence
Validé86
MIT
Complétude README/SKILL.md
Info76
Les métadonnées publiques nécessitent davantage de contexte README/SKILL.md
Risque dépendances/runtime
Validé90
Aucun indice majeur de risque de dépendance dans les métadonnées publiques
Disponibilité de l’installation
Validé92
npx skills add K-Dense-AI/mimeographs --skill david-silver
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Validé100
Aucune surface de permissions à haut risque dans les métadonnées publiques
Preuve du dépôt
Validé86
https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/david-silver
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 K-Dense-AI/mimeographs --skill david-silver
Dépôt
88
https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/david-silver
Licence
86
MIT
Maintenance
88
2 mois depuis le dernier push
Revue IA
55
Core principles contain duplication: the first three principles all express the same 'discard human data to break performance ceiling' idea with cosmetic rewording.
Complétude README/SKILL.md
84
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
100
Aucune surface de permissions à haut risque dans les métadonnées publiques
Activité stars/forks
57
122 stars et 18 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
68
122 stars GitHub
Avertissements
- Core principles contain duplication: the first three principles all express the same 'discard human data to break performance ceiling' idea with cosmetic rewording.
- The skill lacks concrete RL engineering heuristics (e.g., baseline subtraction, eligibility traces, exploration scaling) that are present in the source corpus, making it less actionable for actual ML engineering.
- Frameworks and heuristics sections omit source attributions (src_XXX tags) that would improve traceability and credibility.
- Quality score needs review
- Stars/forks activity: 122 stars, 18 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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