Rapport d’audit du skill
didit-aml-screening Rapport d’audit.
Integrate Didit AML Screening standalone API to screen individuals or companies against global watchlists. Use when the user wants to perform AML checks, screen against sanctions lists, check PEP status, detect adverse media, implement KYC/AML compliance, screen against OFAC/UN/EU watchlists, calculate risk scores, or perform anti-money laundering screening using Didit. Supports 1300+ databases, fuzzy name matching, configurable scoring weights, and continuous monitoring.
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
Avertissement48
26 stars GitHub
Activité stars/forks
Avertissement43
26 stars et 4 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
Échoué36
command execution surface, credential or environment access
Disponibilité de l’installation
Validé92
npx skills add didit-protocol/skills --skill didit-aml-screening
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/didit-protocol/skills/tree/main/skills/didit-aml-screening
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 didit-protocol/skills --skill didit-aml-screening
Dépôt
88
https://github.com/didit-protocol/skills/tree/main/skills/didit-aml-screening
Licence
86
MIT
Maintenance
88
2 mois depuis le dernier push
Revue IA
55
The utility script `screen_aml.py` uses `hit.get('name')` and `hit.get('categories')` but the API response uses `caption` and `datasets` respectively, which may cause incorrect output formatting.
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
36
command execution surface, credential or environment access
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
43
26 stars et 4 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
42
26 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 utility script `screen_aml.py` uses `hit.get('name')` and `hit.get('categories')` but the API response uses `caption` and `datasets` respectively, which may cause incorrect output formatting.
- The script does not handle cases where the `aml` key is missing from the response, which could lead to a KeyError.
- Low GitHub adoption signal
- 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
- GitHub adoption: 26 GitHub stars
- Stars/forks activity: 26 stars, 4 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment 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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