Rapport d’audit du skill
agent-observability-experiment-bootstrap Rapport d’audit.
Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regression, or LLM-as-a-judge scaffolding. The legacy Python invocation remains supported.
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
158 stars GitHub
Activité stars/forks
Avertissement57
158 stars et 25 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
Validé86
Les métadonnées incluent suffisamment de contexte d’usage et de workflow
Risque dépendances/runtime
Avertissement56
credential or environment access, network or browser surface
Disponibilité de l’installation
Validé92
npx skills add datadog-labs/agent-skills --skill agent-observability-experiment-bootstrap
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Échoué34
secrets or environment access, filesystem or document access
Preuve du dépôt
Validé86
https://github.com/datadog-labs/agent-skills/tree/main/agent-observability/agent-observability-experiment-bootstrap
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 datadog-labs/agent-skills --skill agent-observability-experiment-bootstrap
Dépôt
88
https://github.com/datadog-labs/agent-skills/tree/main/agent-observability/agent-observability-experiment-bootstrap
Licence
86
MIT
Maintenance
88
2 mois depuis le dernier push
Revue IA
55
The skill relies on external Datadog SDKs and requires API keys; it should explicitly warn against hardcoding secrets in generated artifacts.
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
56
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
34
secrets or environment access, filesystem or document access
Activité stars/forks
57
158 stars et 25 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
68
158 stars GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Avertissements
- 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
- The skill relies on external Datadog SDKs and requires API keys; it should explicitly warn against hardcoding secrets in generated artifacts.
- The SKILL.md excerpt is truncated, but the provided content is thorough; ensure the full document maintains the same level of detail.
- 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, filesystem or document access
- Stars/forks activity: 158 stars, 25 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: credential or environment access, network or browser surface
- Permission surface: secrets or environment access, filesystem or document access
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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