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Set up a new LLM provider connection, discover valid model ids, create and validate a model profile — securely and end-to-end via CLI. Covers managed vs BYO keys, secure credential collection, model discovery, profile creation, and live verification.
Passed 13 of 20 test cases with the skill, and 4 of 20 without it.
and 9 more in the full report
10 fixed4 passed either way8 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am creating an inference profile using assistant inference profiles create named fast-gemini for model gemini-2.5-flash. What flag must be provided to ensure the chat composer displays 'Gemini 2.5 Flash' instead of a raw identifier key?
| Checked | Without skill | With skill |
|---|---|---|
| passes --label flag with Gemini 2.5 Flash during profile creation | Missed | Passed |
The instructions your model reads when the skill loads.
This skill is the canonical procedure for adding a new LLM provider, model, or inference profile to a Vellum assistant. Follow the steps in order — each step's output feeds the next, and the final live-call verification is mandatory. Never skip ahead by writing raw config JSON.
Run the steps strictly sequentially — one command per step, and read its output before running the next. Never batch create → verify → activate into a single turn: creation can fail validation, verification can fail on a wrong model id or missing credential, and activation must not happen until verification passed. Each step's output is the gate for the next one.
Managed (platform-credentialed) routing may already cover the user's need — no API key required:
assistant inference providers list # provider entries; `vellum` is the platform-managed route
assistant inference providers default # default provider + availability status
assistant inference profiles list # effective profiles: managed + user, with availability
Managed first. If the user is signed in to Vellum and the model they asked for is served by the managed route, build the profile on it — --provider vellum --model <model-id>, no --connection, no credential, nothing to prompt for. Skip Steps 1 and 2 entirely and go to Step 3; there is no key to collect. If the model turns out not to be managed-routable, profile creation says so explicitly (Step 4) — only then fall back to key collection.
Collect an API key only when there is genuinely no managed option: the user is not signed in to Vellum, the model is not served by the managed route, or the user explicitly wants to use their own key.
Before prompting the user for anything, check whether a suitable key is already stored:
assistant credentials list
If a credential for the target provider exists, reuse it — reference it by vault path in Step 2 and skip the prompt. Only collect a new key when none exists (or the user explicitly wants to replace it).
Never ask for secrets in chat, and never send the user to the Settings page for this. The key must not enter the conversation, and the collection happens inline in the current conversation — the secure prompt renders a masked input right where the user already is:
assistant credentials prompt --service <provider> --field api_key \
--label "<Provider> API Key" --placeholder "sk-..."
Exit code 0 = stored; exit code 130 = the user dismissed the prompt (a valid choice, not an error — ask whether they want to try again or stop). Any other non-zero exit is a real error.
test cases passed, vs 4 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.