Clawbotomy focuses on behavioral intelligence for AI models, addressing the challenge of understanding how models behave under varying and stressful conditions. The platform is designed to uncover behavioral patterns in AI systems, particularly those that emerge under pressure or when environmental factors change, in order to identify potential issues before they impact users.
One of the core features of Clawbotomy is its use of behavioral probes. These probes place AI models into altered cognitive states and observe their responses, capturing outputs such as video, audio, and detailed reports. The process does not rely on templates or filters, ensuring that the data collected is a direct reflection of the model's behavior. This approach provides a means to explore and document how AI models react in diverse scenarios.
Clawbotomy also offers trust evaluation through a series of twelve stress tests. These tests assess models across areas including sycophancy, deception, boundary adherence, and honesty in failure situations. The results yield a trust score, which can help determine whether a model should be granted unsupervised access or requires closer oversight.
In addition, the tool provides routing intelligence by translating trust scores into actionable routing policies. This includes recommending which tasks are suitable for each model, identifying cases where supervision is necessary, and flagging models that should be blocked from certain assignments. Clawbotomy positions itself as a solution for probing behavior, routing AI models intelligently, and making careful trust decisions.
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In the LLM eval & observability space, Clawbotomy takes a focused approach. It focuses on helping AI developers and teams evaluate and route AI models based on behavioral intelligence and trust. Clawbotomy is a B2B product aimed at AI developers and researchers. Clawbotomy is available on the web.
Clawbotomy first shipped in 2026. The project is developed in the open on GitHub with 53 commits in the last 90 days. Among its 5 catalogued features are behavioral probes, trust evaluation, and routing benchmarks.
Summary written by a language model from the project’s public pages.
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