creating-online-evaluations

Pass

Audited by Gen Agent Trust Hub on Nov 3, 2026

Risk Level: SAFEINDIRECT_PROMPT_INJECTIONCOMMAND_EXECUTIONDYNAMIC_EXECUTION
Full Analysis
  • [INDIRECT_PROMPT_INJECTION]: The skill configures evaluators to process untrusted data from production AI traffic, such as $ai_generation events, traces, and sessions.
  • Ingestion points: Untrusted content enters the evaluation context through the evaluation_events global in Hog scripts or as input to LLM judges.
  • Capability inventory: Evaluators can execute logic and produce events; the skill uses posthog:execute-sql and posthog:llma-evaluation-create for configuration and verification.
  • Boundary markers: There are no explicit instructions for using delimiters to isolate untrusted data from evaluation instructions.
  • Sanitization: No specific sanitization or validation of the ingested generation data is mentioned.
  • [COMMAND_EXECUTION]: Uses a platform-specific SQL tool to query event counts for verification.
  • Evidence: The skill uses posthog:execute-sql to perform SELECT count() queries to validate the volume of events matching evaluation conditions.
  • [DYNAMIC_EXECUTION]: Involves the creation and testing of user-defined Hog source code.
  • Evidence: Uses posthog:llma-evaluation-test-hog and posthog:llma-evaluation-create to execute and persist evaluation logic provided as strings.
Audit Metadata
Risk Level
SAFE
Analyzed
Nov 3, 2026, 02:29 AM