Google's Developer Relations team published a suite of Agent Skills for Google products on GitHub and outlined five rules for designing trustworthy AI evaluations. The rules emphasize understanding th…
A developer from Google AI detailed a pandas-based pipeline that converts Inspect AI evaluation logs into a CSV optimized for Google Sheets, enabling non-technical stakeholders to create boardroom-rea…
The hex-bench benchmark, a personal evaluation suite for the hex project, tests personal-assistant workflows using Inspect AI's react solver against a local OpenAI-compatible llama.cpp endpoint, with …
A developer from Google Cloud's DevRel team demonstrates how to design objective evaluations for AI agent skills using open-source frameworks like Inspect AI and Harbor. The investigation uses Gemini …
BoundaryBench, a new open-source benchmark from the developer community, measures how much capability coding agents lose when running inside enterprise/NIST-derived hardened sandboxes, with live resul…
EvalPort introduces a grader system with 11 types for LLM evaluation, including exact_match, semantic_similarity, llm_judge, and custom, designed to be framework-agnostic and self-describing. The syst…
OpenEval, a new open-source project, aims to standardize LLM evaluation by defining a portable JSON Schema for test cases, graders, and results. The project provides SDKs, a CLI, and converters for po…
Meridian Labs and Anthropic have developed an extension for the open-source AI safety evaluation framework Petri that enables multi-agent evaluations, addressing a key limitation of the original singl…
AgentThreatBench is a new security benchmark that operationalizes the OWASP Top 10 for Agentic Applications (2026) into executable tasks, designed to measure whether an AI agent can be hijacked by mal…