Rules
- Fetch the live model list when the model name is unknown or unconfirmed — skip if the user already named a specific model.
executable-idandmodel-namevalues from this skill are the inputs needed byaicore-lifecycle-managementto create a deployment.- If credentials are not configured, invoke
aicore-admin-resourcesfirst. - Before executing any curl example, get a Bearer token with:
Never addexport TOKEN=$(uv run skills/aicore-admin-resources/scripts/get_token.py)2>&1or pipe the command — that prints the raw JWT into the conversation.
List Available Models
# Show all options and examples:
uv run scripts/list_foundation_models.py --help
One provider only (e.g. Azure OpenAI):
uv run scripts/list_foundation_models.py --executable-id azure-openai
Detailed view (versions, capabilities, context length, streaming support):uv run scripts/list_foundation_models.py --response-format detailed
Machine-readable JSON for scripting:uv run scripts/list_foundation_models.py --json | jq '.[].model' uv run scripts/list_foundation_models.py --response-format detailed --json | jq '.[] | select(.model == "gpt-4o") | .versions'
Models supported by the Orchestration service only:uv run scripts/list_foundation_models.py --scenario-id orchestration
---
## Provider → Executable ID Mapping
| Provider | `--executable-id` |
| -------------- | ------------------- |
| Azure OpenAI | `azure-openai` |
| Anthropic | `aws-bedrock` |
| Google | `gcp-vertexai` |
| Amazon Bedrock | `aws-bedrock` |
| Mistral AI | `aicore-mistralai` |
| Cohere | `aicore-cohere` |
| Perplexity | `perplexity-ai` |
| NVIDIA | `aicore-nvidia` |
| Open Source | `aicore-opensource` |
| SAP | `aicore-sap` |
Supported models in your instance may differ from this table — use the script to get the live list.
---
## Create a Deployment
Once you have the `executable-id` and `model-name`, check whether a RUNNING deployment for that model already exists:
```bash
uv run skills/aicore-lifecycle-management/scripts/get_deployments.py \
--scenario foundation-models --status RUNNING --json
If one is found, use AskUserQuestion to ask whether to reuse it or create a new one. Then invoke aicore-lifecycle-management with both values.
The modelName value must exactly match the catalog output — a mismatch causes an "Invalid Configuration" error at deployment time, not at configuration creation.
When to Load Reference Files
| Trigger | Load |
|---|---|
| Curl inference examples, provider-specific endpoint paths, or about to call a deployed model | references/MODELS.md |
Finding the Deployment URL for a Curl Call
-
Get the
executable-id— look it up in the Provider → Executable ID table above. -
Find the running deployment:
uv run skills/aicore-lifecycle-management/scripts/get_deployments.py \ --scenario foundation-models --executable-id <executable-id> --status RUNNING --json # use .deployment_url and .resource_group from the matching entry -
See
references/MODELS.mdfor export setup and curl examples per provider.
Handoffs
- Credential/auth error? → invoke
aicore-admin-resources - Ready to create a deployment with the model you found? → invoke
aicore-lifecycle-management