critiqor 0.2.0

Runtime intelligence CLI for reviewing AI agent reliability.

Critiqor

Runtime Intelligence for AI Agents

Observe. Diagnose. Improve.

pip install critiqor

Critiqor helps developers understand whether AI agent runs can be trusted. It observes agent execution, produces a reliability report, and gives teams a clearer way to review agent behavior before relying on the result.

Instead of asking an agent to explain itself after the fact, Critiqor focuses on observable behavior from the run.

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Introduction

AI agents are powerful, but a final answer does not always tell the whole story.

An agent can return something useful while still behaving unreliably during execution. Critiqor gives developers a practical review layer for understanding whether a run looked healthy, risky, inefficient, or worth investigating further.

With Critiqor, you can:

• observe agent runs from the terminal
• review reliability reports in a dashboard
• compare previous runs
• spot behavior that needs developer review
• improve agents with measurable feedback

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Dashboard Preview

After an observation session, Critiqor opens a dashboard that summarizes the run in a format designed for developers and teams.

You can review:

• Executive Summary - the fast answer on whether the run looks healthy
• Trust Assessment - readiness and confidence signals
• Primary Diagnosis - what deserves attention
• Run Review - the observed behavior behind the report
• Recommendations - practical next steps
• Historical Runs - previous observations for comparison

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Installation

Install Critiqor from PyPI:

pip install critiqor

Check the CLI:

critiqor help

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Quick Start

1. Start an observation session

critiqor monitor openclaw

Critiqor starts the OpenClaw workflow and begins observing the run.

2. Use OpenClaw normally

Work with your agent as usual. Critiqor stays out of the way while the agent runs.

3. Finalize the observation

critiqor finalize

Critiqor completes the observation, prepares the reliability report, and opens the dashboard.

4. Reopen previous runs

List historical evaluations:

critiqor runs

Open the latest dashboard:

critiqor dashboard

Open a specific run:

critiqor dashboard run_001

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Features

Terminal-First Workflow

Start and finish agent observations directly from the Critiqor CLI.

Reliability Reports

Review whether a run looks healthy, needs review, or should be treated with caution.

Dashboard Review

Move from terminal execution to a visual report built for debugging, communication, and decision-making.

Historical Runs

Revisit previous observations and compare reliability over time.

OpenClaw Support

Critiqor currently focuses on OpenClaw-based agent workflows.

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When to Use

Use Critiqor when you need to:

• validate agent changes before release
• debug failed or suspicious runs
• compare prompt iterations
• review new agent tools or skills
• catch regressions in behavior
• measure reliability improvements over time
• explain agent behavior to teammates or stakeholders
• decide whether an agent run is ready for production workflows

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Trust & Privacy

Critiqor is designed around explicit observation.

Developers control when observation starts, when it ends, and which results they review or share. Critiqor provides reliability signals to support developer judgment; it does not replace tests, human review, or production monitoring.

Principles:

• observation should be explicit
• reports should be grounded in the observed run
• developers should be able to review the result
• sensitive workflow data should remain under user control
• reliability reports should support human decision-making

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Philosophy

Critiqor is built on a simple belief:

Reliable agents should be evaluated by what they do, not what they say they did.

That means:

• evaluate observable behavior
• prioritize evidence over self-reporting
• make reliability easier to explain
• improve through measurement
• help developers review the work behind the answer

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FAQ

What is Critiqor?

Critiqor is an AI Agent Runtime Intelligence Platform. It helps developers observe agent runs and review reliability reports.

Which workflows are supported?

Critiqor currently supports OpenClaw-focused observation workflows.

How do I install Critiqor?

pip install critiqor

What does the dashboard show?

The dashboard shows an executive summary, trust assessment, primary diagnosis, run review, recommendations, and historical runs.

How should I interpret trust levels?

Trust levels are reliability signals based on the observed run. They help you decide whether a run looks healthy, needs review, or may be risky.

Can I review previous runs?

Yes. Use:

critiqor runs
critiqor dashboard run_001

Does Critiqor replace tests?

No. Critiqor complements tests by helping you review how an agent behaved during a run. Use it alongside unit tests, integration tests, evals, and human review.

How do I report bugs?

Open a GitHub issue with:

• your Critiqor version
• your Python version
• the command you ran
• what you expected
• what happened instead

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Contributing

Critiqor is early and evolving quickly.

Useful contributions include:

• bug reports
• documentation improvements
• OpenClaw workflow feedback
• dashboard usability feedback
• integration requests

If you are proposing a larger change, please open an issue first so the direction can be discussed.

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License

Critiqor is released under the MIT License. See LICENSE for details.