How model capability monitoring works

Model-internal monitoring needs access to the model runtime. WoolyAI runs inside the address space of the inference environment serving the open-source model and reads internal signals while the model is generating.

How it works

1APPYour agentor applicationRequestResponseYOUR INFERENCE ENVIRONMENTvLLM and other runtimes you host2MODEL SERVER3Capability monitoring4SIGNALSCodeTool callCyberfoundAnd more5YOUR POLICYAllowAlertSandboxStopYour policy acts on the response before generation completes

Will it work in my setup?

Supported

You control the model serving

  • Open-source and open-weight models
  • Self-hosted inference
  • Private cloud or VPC-based inference
Not supported

Closed model APIs

  • OpenAI-hosted ChatGPT and the OpenAI API
  • Anthropic-hosted Claude
  • Google-hosted Gemini API

You do not control the model’s inference runtime.

But I use the OpenAI API format

The request format does not matter. Where the model runs does.

Supported

Self-hosted, OpenAI-compatible

Yes. vLLM serving Qwen at /v1/chat/completions can look like the OpenAI API to your application. WoolyAI still has access to the model runtime underneath.

Not supported

api.openai.com

Different case. You do not control that model execution, so you cannot read its internal state.

Why model runtime access matters

Internal neuron signals are only visible within the model serving. Input and output monitoring only see the edges and the response is generated.

Prompt inWoolyAI reads internal signals at every step of generationAlert or block here, before generation completesOutput outInput monitoringOutput monitoringInput and output monitoring only see the edges

See capability monitoring on a live model.