METR · July 24, 2026

Metrics of Agent Ability

Why it matters

METR organizes agent-capability measures around performance as a function of expenditure, comparing fixed-budget scores, cost to reach a score, returns to test-time scaling, human-equivalent time and expenditure horizons, and human-relative cost. It explains when familiar benchmark scores break down—particularly when performance keeps improving with more inference or human benchmarks saturate—and notes that full cost, reliability, coverage, and elicitation choices affect the result.

My takeaway: Do not compare agents on pass rate alone when test-time compute varies. Plot score against total expenditure, state the elicitation budget, pair capability with cost and reliability, and use a human-grounded metric only where the human comparison remains meaningful.
Keep exploring

More curated notes connected through Model Evaluation and Agent Security.

OWASP GenAI Security Project · guide

OWASP Top 10 for Agentic Applications for 2026

OWASP's community guide organizes agentic-system risk into ten categories, including goal hijacking, tool misuse, identity and privilege abuse, memory poisoning, insecure inter-agent communication, cascading failures, and rogue-agent behavior. It provides a shared taxonomy and mitigation starting point rather than a certification checklist or evidence that a deployed system is secure.

OWASP GenAI Security Project · tool

FinBot CTF Is Live: A Hands-On Companion to the OWASP GenAI Security Project

OWASP FinBot is a hands-on agentic-security CTF built around a simulated multi-agent financial-services platform with real tool access. Its challenges cover prompt injection, tool misuse, policy bypass, data exfiltration, privilege escalation, remote code execution, shared context, and compromised MCP servers.

Google Cloud Security Blog · tool

Now in preview: Find and fix software vulnerabilities with CodeMender

Google opened a preview of CodeMender, an AI code-security agent delivered through Gemini Enterprise Agent Platform and AI Threat Defense. It is designed to inspect code, identify and validate potentially exploitable defects, and produce targeted fixes, with Google’s specialized Gemini 3.5 Flash Cyber model initially restricted to governments and trusted partners.