Know where the context goes.
An unfiltered AI coding workflow still has a concrete model, endpoint, and set of tool permissions. The words "uncensored" and "local" do not establish how a particular setup behaves. Inspect the configuration that actually handles your requests.
Trace the request route
Record the provider, base URL, and model identifier without displaying credentials. Determine whether requests go directly to the provider or through a gateway. Check the selected service documentation for retention, context limits, and supported tool use. Provider behavior and policies depend on the chosen setup.
Separate model access from tool access
A model response is different from permission to read files, run commands, or contact services. Inspect those controls independently. Begin with a public or disposable project and a read-only task. Local inference may reduce remote model traffic, but connected tools can still send data elsewhere.
Checkpoint
- Endpoint and model verified
- Credential storage understood
- File and command permissions reviewed
Read-only transmission
Explain which configured endpoint and model would process this task. Do not reveal keys or tokens. List the context and tools the task needs, and identify any routing or retention details that cannot be established from available configuration.
There is no universal promise of unrestricted behavior. Evaluate the exact provider, model, client, and connected tools together.
Next: Review queue