Individual skill

using-model-endpoint

Call a registered model endpoint over its native HTTP API from the endpoint's scoped inference kernel (BASE_URL preloaded). Load once a task needs predictions from a registered model endpoint.

configs/microservice/bff-service/configs/agent-skills/claude-science/using-model-endpoint/SKILL.md

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Observed behavior: Local scripts
Last checked: Nov 3, 2026

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Repository stars (not skill ratings): 2,385
Repository last updated: Nov 6, 2026
License: Apache-2.0

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You are a **pure HTTP client of `BASE_URL`**. Each registered model endpoint
gets its own inference kernel — a Python REPL whose network egress is scoped
to exactly that endpoint — reached via
`compute_provider({'provider': '<slug>', 'code': '…'})` (`<slug>` from
`list_compute`, without the `infer:` prefix).

- `BASE_URL` is preloaded (as a Python variable AND as
  `os.environ["BASE_URL"]`) — build request URLs from it, never hardcode
  hosts/ports. Call the model's **native API** with `httpx` (preinstalled)
  or `requests`; request shapes live in the provider's own runbook skill
  (the registration's `skillName`).
[Credential-related source omitted]
  canonical env name when a credential is delivered; the credential's own
  name is usually aliased too). Local endpoints need no auth header.