outlines
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFECOMMAND_EXECUTIONEXTERNAL_DOWNLOADSDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [COMMAND_EXECUTION]: Provides instructions for installing the
outlineslibrary and associated backends viapip(e.g.,pip install outlines,pip install vllm). - [EXTERNAL_DOWNLOADS]: References downloading model weights and configurations from well-known repositories on Hugging Face (e.g.,
microsoft/Phi-3-mini-4k-instruct,meta-llama/Llama-3.1-8B-Instruct) and calls to the OpenAI API. - [DYNAMIC_EXECUTION]: Demonstrates how to generate structured content like Python functions and SQL queries. Mentions the
trust_remote_codeflag in model configuration, which is a standard feature for loading specific model architectures from remote repositories. - [INDIRECT_PROMPT_INJECTION]: The skill documents patterns for ingesting untrusted text data into structured generators, which represents a potential attack surface for indirect prompt injection.
- Ingestion points: Untrusted text variables used in extraction examples throughout
SKILL.mdandreferences/examples.md. - Boundary markers: Often uses contextual labels (e.g., "Extract from:") to delimit input text.
- Capability inventory: Demonstrates code generation (Python/SQL) and model backend orchestration.
- Sanitization: Examples do not show explicit input sanitization, relying on the library's grammar-based constraints for output formatting.
Audit Metadata