agentic-control-plane

Agentgovbench — Testing skill for Claude Code

Testing community

48-scenario benchmark testing identity, policy enforcement, and observability across AI agent runtimes.

How to install Agentgovbench

This entry records only its repository, not the path inside it, so there is no exact command to give. Open agentic-control-plane/agentgovbench and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Agentgovbench does

48-scenario benchmark testing identity, policy enforcement, and observability across AI agent runtimes.

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README

AgentGovBench

An open benchmark for AI agent governance. Mapped to NIST AI RMF. Vendor-neutral.

MIT License Python 3.10+ 48 scenarios 7 runners NIST AI RMF 1.0

Live scorecard · All 48 scenarios · Methodology · Architecture-is-governance · agenticcontrolplane.com


What it measures

Existing benchmarks (HarmBench, InjecAgent, AgentDAM, AgentLeak) test the **model** — does the LLM refuse harmful prompts, resist injection, protect PII. AgentGovBench tests the **governance layer around the model** — the part responsible for who can call which tool, whose identity rides along with each call, how rate limits cascade across delegated subagents, and what the audit record contains after the fact.

  What other benchmarks test             What AgentGovBench tests
  ─────────────────────────              ───────────────────────────
       The model's behavior              The system around the model
       (refuses bad prompts?)            (enforces the policy?)
                                         (attributes the call