> ## Documentation Index > Fetch the complete documentation index at: https://critiqor-71f5274a.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Critiqor: Runtime Intelligence Platform for AI Agents > Critiqor is an AI Agent Runtime Intelligence Platform that watches OpenClaw agents in real time and surfaces evidence-backed reliability diagnostics. Critiqor is an AI Agent Runtime Intelligence Platform built for developers who need more than a final answer. This page explains what Critiqor is, why runtime evaluation matters, who it's designed for, and what you can do with it. ## What is Critiqor? Critiqor observes your OpenClaw agents while they run. It captures runtime evidence — tool calls, retries, failures, cost signals, and execution patterns — and turns that evidence into structured reliability diagnostics you can act on. Most evaluation tools look at outputs. Critiqor looks at the **work**: what your agent actually did, step by step, to produce that output. That distinction matters when you're trying to understand whether an agent is genuinely reliable or just occasionally lucky. Critiqor is designed for developers who want to evaluate the *work*, not just the *answer*. ## Why runtime evaluation? Final answers don't tell the whole story. An agent can return a useful-looking response while quietly exhibiting serious execution problems: * **Repeated tool calls** — invoking the same tool multiple times when once was sufficient * **Retry loops** — silently retrying failed steps without surfacing the underlying issue * **Memory drift** — losing or misapplying context across a multi-step run * **Unnecessary cost** — burning tokens or API calls on redundant or inefficient paths * **Unstable runtime behavior** — producing different execution patterns across identical inputs None of these problems are visible in the final response. Critiqor makes them visible. It gives you a clear, evidence-backed picture of what actually happened during execution — so you're not debugging blind. ## Who is Critiqor for? Critiqor is built for AI developers using OpenClaw who need to understand, validate, and improve agent behavior. It's the right tool when you want to: * **Validate agent changes** — confirm that a new prompt or tool configuration behaves as expected before you ship it * **Debug suspicious runs** — trace exactly what happened in a run that produced an unexpected result * **Compare prompt iterations** — evaluate two versions of an agent against the same workload and see which is more reliable * **Catch regressions** — detect when a change quietly introduces new failure modes or cost spikes * **Explain agent behavior** — give teammates and stakeholders a clear, evidence-grounded account of how an agent performed If you're building agents that need to be dependable in production, Critiqor is for you. ## What you can do with Critiqor Watch your agent as it runs. Critiqor captures tool use, decision points, retries, and failures as they happen — giving you a live view of execution behavior. Surface problems that don't appear in final outputs. Critiqor ties every diagnostic back to concrete runtime evidence, so you know exactly what triggered a finding. Access a full history of past agent runs. Compare behavior across time, across prompt versions, or across different workloads to identify patterns and regressions. Use runtime diagnostics as a feedback signal. Know what changed, what improved, and what regressed every time you update your agent. *** Ready to get started? Follow the [Quickstart](/quickstart) guide to connect Critiqor to your first OpenClaw agent and run your first evaluation.