Rapport d’audit du skill
ml-autoresearch Rapport d’audit.
Use when the user wants an autonomous ML research loop that does more than blindly try changes. After every training run the agent analyses what actually happened inside the model — gradients, activations, embeddings, errors, data — and grounds the next change in that evidence. A `<literature>` on/off dial adds scientific-literature grounding: off behaves as a pure analysis-first loop; on searches papers, grades the evidence, and implements only what prior work supports. One change per run; loops forever until interrupted. Not for one-off training runs or hyperparameter sweeps.
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
Info64
credential or environment access, network or browser surface
Disponibilité de l’installation
Validé92
npx skills add gaasher/Agent-Loop-Skills --skill ml-autoresearch
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Échoué22
secrets or environment access, shell or command execution
Preuve du dépôt
Validé86
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/ml-autoresearch
État de revue
Validé88
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 ml-autoresearch
Dépôt
88
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/ml-autoresearch
Licence
86
MIT
Maintenance
76
4 mois depuis le dernier push
Revue IA
88
Approved with no listed issues
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
64
credential or environment access, network or browser surface
Sécurité de la commande d’installation
92
Chemin d’installation standard de package ou runtime
Surface de permissions
22
secrets or environment access, shell or command execution
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
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- 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
- Stars/forks activity: 163 stars, 19 forks; issue activity unavailable in current metadata
- Permission surface: secrets or environment access, shell or command execution
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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