Skill v1.0.0

version: "1.0.0" name: llm-provider-integration description: > Adding an LLM provider to RedAmon: the credential boundary (keys must never reach scan containers), prefix-routed model ids, and the provider registry. A misrouted model id or a leaked key are the two failures this guards. Trigger: adding or editing an LLM provider; editing parse_model_provider in agentic/orchestrator_helpers/llm_setup.py, the webapp provider-type registry, the user_llm_providers model, or an LLM call site that passes an API key; a non-chat provider type (TypeSafe Jev) or a path that picks "any provider row". license: MIT metadata: author: redamon version: "1.0.0" scope: [agentic, webapp] auto_invoke:

• "Adding or integrating an LLM provider"
• "Editing model-id routing or provider credential handling"
• "Adding a non-chat provider type, or a path that picks any provider row"

When to Use

• Adding a new LLM provider (OpenAI-compatible or otherwise) the agent can use.

For a non-LLM external API tool, use agentic-tool-integration.

Critical Rules

• NEVER let a provider API key reach a scan container. Keys live in exactly

two places: Postgres user_llm_providers rows and, in transit, on the wire between webapp and agent. The recon / scan / MCP containers must never see them. Do not thread a provider key through recon settings or container env.

• NEVER add a model id that is not prefix-routed. Anything other than

claude-* and bare OpenAI ids MUST carry a provider/<model> prefix, resolved by parse_model_provider() at agentic/orchestrator_helpers/llm_setup.py:67. An unprefixed id routes to the wrong provider silently.

• NEVER treat every `user_llm_providers` row as a chat LLM. A non-chat type

(today jev, the TypeSafe decision API) must be skipped by every path that builds a chat model, or its token is sent to the wrong host: setup_llm's custom branch builds ChatOpenAI(api_key=<row key>) with no base URL, which is api.openai.com. Add the type to NON_CHAT_PROVIDER_TYPES in BOTH twins (agentic/llm_builder.py, webapp/src/lib/llmProviderKinds.ts); use chat_providers() / isChatProvider wherever rows are listed, counted, gated or forwarded (the /api/models forward, the project LLM gate, the triage preflight, the feature-model grid); and never let a stale custom/<id> fall back to "the first provider" (custom_provider_or_fallback falls back only to custom-capable types). setup_llm also refuses a non-chat type outright.

• A non-chat provider's endpoint is a constant, and its type is locked.

agentic/jev_client.py is the only code that talks to api.typesafe.ai: a fixed base URL, no redirects, fixed error texts. On the webapp, POST forces model, URL and headers and allows one row per user; PUT and the test route refuse a type change in either direction and ignore a body-supplied URL/headers for a stored row, so a stored token can never be re-pointed at another host.

• ALWAYS register the provider in the webapp provider-type registry and

propagate the key kwarg into every LLM call site. A provider registered but not propagated builds a client with no credentials. The guide enumerates all 11 integration points; touch each.

The two invariants

Commands

docker compose build agent && docker compose up -d agent   # agentic/ is baked
docker compose exec webapp npx prisma db push              # provider schema changes (NEVER prisma migrate)

Resources

• docs/readmes/coding_agent_prompts/PROVIDER_INTEGRATION_GUIDELINES.md - the 11 integration points, decision tree, and model-id prefix table
• Related skill: agentic-tool-integration