Skill Detail
Probe ML and LLM systems for regressions and vulnerabilities with Giskard
Run automated red-team and failure scans against an LLM or RAG app before users find the breakage.
Security & VerificationMulti-Framework
Security & Verification
Multi-Framework
Security Reviewed
Tool match: giskard-oss
⭐ 5.3k GitHub stars
Apache-2.0 license
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill probe-ml-and-llm-systems-for-regressions-and-vulnerabilities-with-giskard
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Python environment, Giskard open-source package, model or RAG application access, test datasets or prompts, model provider credentials where required
Install & setup
Install the Giskard open-source package in a Python environment, connect it to the target model or RAG workflow, then run the documented scan or evaluation flows and review the reported failures.
Author
Giskard AI
Publisher
Organization
Last updated
Apr 15, 2026
Quick brief
Use Giskard when an agent needs to probe an LLM or RAG system for security issues, business-logic failures, and regression-prone behavior before release. The workflow is not generic model development. It is targeted testing: generate or run scanning suites, review failing cases, and harden the system. That scope boundary, red-teaming and failure detection for AI behavior, keeps it distinct from broad ML platforms and generic evaluation dashboards.