foundations-queueing-theory

Pass

Audited by Gen Agent Trust Hub on Aug 12, 2026

Risk Level: SAFECOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
  • [COMMAND_EXECUTION]: The skill instructs the agent to execute a local Python script (agents-skills-feedback-loop/scripts/append_learning.py) to record insights into the learnings.md file. This creates an instruction-based surface for executing code on the local system.
  • [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process performance metrics (e.g., arrival rates, service times) that are interpolated into its reasoning logic for capacity planning.
  • Ingestion points: Numeric performance data (λ, μ, ρ, CV²) provided by the user in the context of the queueing theory playbooks.
  • Boundary markers: None identified; inputs are used directly in mathematical calculations and expert judgment reasoning.
  • Capability inventory: The skill enables file modification of learnings.md and local script execution through the feedback workflow.
  • Sanitization: No input validation or sanitization mechanisms are defined for the metrics processed.
Audit Metadata
Risk Level
SAFE
Analyzed
Aug 12, 2026, 09:10 PM
Security Audit — agent-trust-hub — foundations-queueing-theory