using-model-endpoint
Call a configured Feynman model endpoint and interpret its response. Use when a task needs inference from a registered endpoint, remote model API, local model service, or custom connector-backed predictor.
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tessl review fix ./skills/using-model-endpoint/SKILL.mdUsing Model Endpoint
Use this skill after a model endpoint is already configured or explicitly chosen.
Workflow:
- Confirm endpoint identity, auth status, input schema, output schema, model version, and rate/size limits.
- Build a minimal request with explicit inputs and no hidden context.
- Save request metadata, response, latency, status, and parsing code as artifacts without exposing secrets.
- Validate response shape and handle model errors as evidence, not as missing work to hide.
- Interpret predictions separately from source-backed facts.
When the endpoint is not configured, switch to managed-model-endpoints or compute-env-setup instead of pretending inference ran.
- Repository
- companion-inc/feynman
- Commit
95c51d9
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- First committed
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