Skills when-training-neural-networks-use-flow-nexus-neural
📦
when-training-neural-networks-use-flow-nexus-neural
Content revision r1 Medium Risk 🔑 Env variables⚙️ External commands🌐 Network access
Entraîner des réseaux de neurones avec Flow Nexus
L'entraînement distribué de réseaux de neurones nécessite une configuration, une validation et un déploiement coordonnés. Cette skill guide les workflows Flow Nexus, de la conception de l'architecture au service en production.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "when-training-neural-networks-use-flow-nexus-neural" from https://skillstore.io/skills/dnyoussef-when-training-neural-networks-use-flow-nexus-neural.md and its manifest at https://skillstore.io/api/skills/dnyoussef-when-training-neural-networks-use-flow-nexus-neural/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "when-training-neural-networks-use-flow-nexus-neural". Entraîner un classifieur transformer avec Flow Nexus et le préparer pour le service.
Expected outcome:
Un plan par phases couvrant l'authentification, la configuration du cluster, le choix de l'architecture, l'entraînement distribué, les métriques de validation et la préparation au déploiement.
Using "when-training-neural-networks-use-flow-nexus-neural". Examiner si mon modèle entraîné est prêt pour la production.
Expected outcome:
Un résumé de validation avec la précision, la latence, les vérifications de surapprentissage, l'état du benchmark et les actions de déploiement recommandées.
Using "when-training-neural-networks-use-flow-nexus-neural". Créer un transfert de déploiement pour un projet de réseau de neurones terminé.
Expected outcome:
Un plan de transfert avec les métadonnées du modèle, les endpoints de service, les attentes de surveillance, les health checks et les précautions opérationnelles.
Security Audit
Medium Riskv8 • 7/5/2026 Open versioned report
Most static detections are Markdown fences, workflow diagrams, local URLs, or illustrative labels rather than malicious code. Confirmed concerns are documented commands that may execute unpinned npx packages and a deployment example that can expose an unauthenticated inference service. No prompt injection or secret exfiltration intent was found.
4
Files scanned
1,664
Lines analyzed
15
Review items
0
False positives ignored
Confirmed security concerns (2)
Medium
Unpinned Remote Package Execution
The SOP asks users or agents to run npx flow-nexus@latest and npx claude-flow@alpha. These dist-tags can execute package code that changes over time without a pinned version.
The cited commands directly invoke npm packages through mutable latest and alpha tags. This is a clear supply-chain risk when automated by an agent.
Medium
Unauthenticated Inference Service Exposure
The deployment example binds Uvicorn to all interfaces and maps port 8000 while exposing prediction and metrics endpoints without authentication.
The service binds to 0.0.0.0 and the deploy script publishes the port. The FastAPI example shows health, predict, and metrics routes with no access control.
Capability review items (15)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Medium
Shell command substitution
npx claude-flow@alpha hooks session-restore --session-id "neural-training-$(date +%s)"
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"complete\", \"cluster_id\": \"[id]\", \"timestamp\": \"$(date -Iseconds)\"}"
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
CLUSTER_ID=$(npx claude-flow@alpha memory retrieve --key "neural/cluster-id" | jq -r '.value')
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"complete\", \"nodes\": 4, \"topology\": \"mesh\", \"timestamp\": \"$(date -I
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
CLUSTER_ID=$(npx claude-flow@alpha memory retrieve --key "neural/cluster-id" | jq -r '.value')
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
STATUS=$(npx claude-flow@alpha memory retrieve --key "neural/training-status" | jq -r '.value')
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"complete\", \"training_job\": \"$TRAINING_JOB_ID\", \"final_accuracy\": 0.94
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
CLUSTER_ID=$(npx claude-flow@alpha memory retrieve --key "neural/cluster-id" | jq -r '.value')
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
TRAINING_METRICS=$(npx claude-flow@alpha memory retrieve --key "neural/training-metrics" | jq -r '.v
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"inference_latency_ms\": 67, \"throughput_qps\": 1200, \"memory_mb\": 512, \"timestamp\":
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"complete\", \"validation_passed\": true, \"accuracy\": 0.94, \"latency_ms\":
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"model_id\": \"$TRAINING_JOB_ID\", \"template_published\": true, \"timestamp\": \"$(date
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"complete\", \"deployment\": \"docker\", \"api\": \"fastapi\", \"port\": 8000
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Shell command substitution
--value "{\"status\": \"success\", \"model_accuracy\": 0.94, \"latency_ms\": 67, \"deployed\": true,
This documented shell example invokes npx claude-flow@alpha while using command substitution. Running unpinned package commands from a skill can execute changing third-party code in the user environment.
Medium
Hardcoded IP address
CMD ["uvicorn", "serve:app", "--host", "0.0.0.0", "--port", "8000"]
The Dockerfile example binds Uvicorn to 0.0.0.0, and the deployment script maps port 8000. If copied as-is, it can expose an unauthenticated inference API.
Risk Factors
🔑 Env variables (1)
⚙️ External commands (87)
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🌐 Network access (10)
Audited by: codex View Audit History →
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APA citation
DNYoussef. (2026). when-training-neural-networks-use-flow-nexus-neural security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dnyoussef-when-training-neural-networks-use-flow-nexus-neural/audits/8BibTeX citation
@techreport{dnyoussef-dnyoussef-when-training-neural-networks-use-flow-nexus-neural-2026,
author = {DNYoussef},
title = {when-training-neural-networks-use-flow-nexus-neural security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/dnyoussef-when-training-neural-networks-use-flow-nexus-neural/audits/8},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "when-training-neural-networks-use-flow-nexus-neural security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "DNYoussef"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/dnyoussef-when-training-neural-networks-use-flow-nexus-neural/audits/8"
identifiers:
- type: other
value: "skillstore:dnyoussef-when-training-neural-networks-use-flow-nexus-neural:audit:8"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
72
Community
74
Spec Compliance
What You Can Build
Planifier un entraînement distribué
Créer un plan d'entraînement structuré avec les étapes d'architecture, de jeu de données, de validation et de benchmark.
Coordonner les ressources Flow Nexus
Cartographier la configuration du cluster, le déploiement des noeuds, la coordination de la mémoire et les opérations d'entraînement distribué.
Préparer le service du modèle
Rédiger la documentation Docker, FastAPI, de health check, de métriques et de déploiement pour un modèle entraîné.
Try These Prompts
Planifier une exécution d'entraînement
Utilise cette skill pour planifier une exécution d'entraînement de réseau de neurones Flow Nexus pour ma tâche, mon type de jeu de données, ma précision cible et mon objectif de déploiement.
Configurer l'architecture
Utilise cette skill pour proposer l'architecture du modèle, les hyperparamètres, les vérifications de validation et les ressources Flow Nexus pour mon réseau de neurones.
Valider et benchmarker
Utilise cette skill pour concevoir les tests de validation, les benchmarks de performance, les seuils d'acceptation et les étapes de dépannage pour mon modèle entraîné.
Préparer le déploiement en production
Utilise cette skill pour produire une checklist de déploiement sécurisé, un plan d'API de service, un plan de surveillance et des étapes de rollout pour mon modèle entraîné.
Best Practices
- Remplacez tous les ID de modèle, identifiants, métriques et valeurs de jeu de données placeholders avant d'exécuter des commandes.
- Épinglez les versions des packages et vérifiez les commandes shell avant d'autoriser un agent à les exécuter.
- Ajoutez l'authentification, les contrôles d'accès et l'observabilité avant d'exposer un service d'inférence.
Avoid
- Exécuter les exemples de commandes de déploiement sans modification dans un environnement partagé ou de production.
- Considérer les chiffres illustratifs de précision, de latence et de débit comme de véritables preuves de validation.
- Publier des endpoints de modèle sans authentification, limites de débit, surveillance ni plans de rollback.
Frequently Asked Questions
À quoi cette skill aide-t-elle ?
Elle aide à planifier et exécuter un workflow de réseau de neurones Flow Nexus, de la configuration au déploiement.
Entraîne-t-elle un modèle toute seule ?
Non. Elle fournit des instructions de workflow et des exemples qui nécessitent les outils Flow Nexus et des données fournies par l'utilisateur.
Quels outils sont mentionnés ?
Elle fait référence aux actions Flow Nexus MCP, aux hooks Claude Flow, aux sandboxes E2B, à Docker, FastAPI et aux concepts de service TensorFlow.
Puis-je l'utiliser avec Claude Code ou Codex ?
Oui. Elle est écrite comme une skill procédurale pour des workflows compatibles Claude, Claude Code et Codex.
Que dois-je vérifier avant d'exécuter des commandes ?
Vérifiez les versions des packages, les scripts shell, les paramètres Docker, l'exposition réseau, les identifiants et les chemins de fichiers locaux.
Est-elle adaptée au déploiement en production ?
Elle peut prendre en charge la planification de production, mais les utilisateurs doivent ajouter les contrôles de sécurité, la gouvernance, les tests et la revue opérationnelle.
Developer Details
Author
DNYoussefLicense
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
c579efd02184f1128d6741d16e6c8d951d7d4208
Maintenance freshness
7/22/2026
Usage
7 downloads · 331 views
File structure