online-evals
Pass
Audited by Gen Agent Trust Hub on Oct 27, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONCOMMAND_EXECUTIONEXTERNAL_DOWNLOADS
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill defines a workflow for LLM-as-a-judge evaluations, which creates a surface for indirect prompt injection where malicious content in evaluated data could influence the judge's scoring or reasoning.
- Ingestion points: The skill ingests untrusted data via the
input_textandoutput_textparameters in the Python SDK examples and the judge message content defined inSKILL.md. - Boundary markers: No specific delimiters or boundary instructions are provided to separate the evaluation criteria from the untrusted data being analyzed.
- Capability inventory: The skill possesses the capability to modify LaunchDarkly project configurations, update targeting rules, and record metrics via REST API calls and SDK methods.
- Sanitization: There are no instructions for sanitizing or filtering the content provided to the judges before evaluation.
- [COMMAND_EXECUTION]: Provides shell commands using
curlto interact with LaunchDarkly's beta REST API for creating configs, managing variations, and updating targeting instructions. - [EXTERNAL_DOWNLOADS]: References and provides links to official LaunchDarkly GitHub repositories and documentation for SDK implementation examples.
Audit Metadata