Scaffold project

Quarkus + LangChain4j Scaffolding

Version: 0.13.1

Prerequisites. The Quarkus Agents MCP, context7, and the project conventions file (CLAUDE.md for Claude, AGENTS.md for Codex) should already be configured — if they are not, run /setup-agentic-scaffolding first. Invoke this skill as /scaffold-project, or as /quarkus-agentic-scaffolding:scaffold-project when it is installed as a plugin; it also triggers automatically when you ask to create a project or add a component.

Gate: verify the MCP first

Do this before anything else — before reading the project, before §1. Scaffolding is Quarkus work, so the Quarkus Agents MCP is mandatory (conventions §1). VERIFY it is reachable: confirm the quarkus_* tools are present in your toolset and that a cheap call (e.g. quarkus_status) succeeds. If the tools are absent or the call fails, STOP immediately: report exactly what is missing, point the user to /setup-agentic-scaffolding (and to restarting the session after registering it, since MCPs load at session start), and end the turn. A missing or unreachable MCP is never permission to proceed manually — do not fall back to the Quarkus CLI, Maven/Gradle archetypes, model memory, or web search, and do not offer to "continue without it". Only once the gate passes do you continue below.

1. When to use this skill

This skill has two roles:

• Create a Quarkus + LangChain4j project end-to-end — scaffold, bootstrap, initialize, generate, or kickstart a new project or module, from quarkus_create through a running, test-green dev mode (§2–§3, §11–§13).
• Add a component to an existing project — a new AI service (§4), tools (§5), MCP client (§6) or server (§7), agent or multi-agent workflow (§8), RAG pipeline (§9), guardrails (§10), or embedding store. These requests auto-trigger the skill.

It covers how to lay things out and get them running. It does not restate coding conventions — see §14.

Everything here goes through the Quarkus Agents MCP and context7 (see the prerequisites note above): create projects and discover extensions with quarkus_create / quarkus_searchTools, call quarkus_skills for each chosen extension before writing any code, and look up LangChain4j and other library APIs with context7. The Quarkus Agents MCP itself is a hard prerequisite — verify it up front per the Gate above; if any other required tool is unavailable, stop and report it rather than guessing.

2. Project layout convention

Single-module Quarkus application (no multi-module reactor by default). Organize one root package into focused sub-packages:

src/main/java/<group>/<app>/
  ai/         # @RegisterAiService interfaces (AI services and agents)
  tools/      # @Tool CDI beans the AI services can call
  guardrails/ # input/output guardrails (optional)
  mcp/        # MCP server features (@Tool/@Prompt/@Resource offered to remote MCP clients)
  dto/        # records: inputs, reports, and event/step types
  workflow/   # agentic orchestrators + the streaming-bridge beans
  rest/       # JAX-RS resources (@Path)
  web/        # WebSocket endpoints (@WebSocket)
  rag/        # RagConfig producers (only when escalating beyond Easy RAG)
  memory/     # chat-memory store + provider (optional, persistent memory)
src/main/resources/
  application.properties
  rag/        # documents folder ingested by Easy RAG (quarkus.langchain4j.easy-rag.path)

Start with only the sub-packages a feature needs; add the rest as the project grows. This layout is owned by the skill — quarkus_create does not impose it.

3. Creating a new project

Create the project through the Quarkus Agents MCP quarkus_create — never by hand, and never with Maven, Gradle, or the Quarkus CLI. quarkus_create both generates the project and auto-starts dev mode, so run the steps below in order.

Required parameters. quarkus_create takes outputDir, noCode, and noWrapper. Present these recommended defaults to the user and confirm before generating:

• noCode=true — this repo's opinionated templates (§4–§13) replace the codestart hello-world, so skip the generated sample code.
• noWrapper=false — keep the Maven Wrapper (mvnw) so the project builds without a local Maven install.
• outputDir — the target directory for the new project.

Choose the Quarkus version up front. There is no streams parameter. Decide LTS vs. latest with the user before generating: pass quarkusVersion explicitly to pin a release — pick the current LTS from the Quarkus release/support policy rather than hardcoding a number that will rot — or omit quarkusVersion to take the latest platform release.

Extension selection is a mandatory user gate. quarkus_create's own contract requires the extension list to be chosen, not assumed. Present this capability-based menu with the recommended default and wait for the user's choice before generating:

• core (recommended default): rest, rest-jackson, smallrye-openapi, websockets-next, langchain4j-ollama
• agents: add langchain4j-agentic
• RAG: add langchain4j-easy-rag
• MCP client: add langchain4j-mcp
• MCP server: add mcp-server-http (io.quarkiverse.mcp; use mcp-server-stdio for a subprocess server)
• observability (optional): add micrometer-registry-prometheus and opentelemetry
• fault tolerance (optional): add smallrye-fault-tolerance

(quarkus-arc comes in automatically.) The generated pom.xml already imports the quarkus-bom and quarkus-langchain4j-bom platform BOMs, sets Java 25, enables the -parameters compiler flag, adds a native profile, and pulls in the test stack (quarkus-junit + rest-assured) — all at the resolved platform version. Do not hand-maintain any of that: quarkus_create (the same codestart generator behind code.quarkus.io) keeps it up to date.

Put the generated project under git immediately. Before any further MCP call, run git init && git add -A && git commit inside the generated project directory — the Quarkus Agents MCP refuses to operate on a project that is not under git control, so quarkus_start and quarkus_skills fail until this is done.

Learn each extension's patterns before writing code. Call quarkus_skills for every selected extension (comma-separated queries are supported) before scaffolding against it — this is mandatory, not optional — and use context7 for LangChain4j and other library API lookups.

Add the non-extension dependencies. Project generators add only Quarkus extensions, so add the dev.langchain4j dependencies from templates/pom.xml.template by hand: the embedding model (required by Easy RAG) and, for PDF ingestion, the document parser.

Then lay out the sub-packages (§2), drop in the templates you need (§4–§10), write the application.properties baseline (§11), and verify (§12).

4. AI service scaffolding

Use templates/AiService.java.template. It is a @RegisterAiService interface with @SystemMessage / @UserMessage prompts and a typed return value, plus an optional @RegisterAiService(modelName = "…") for selecting a named model. Pair it with a rest/ resource or a web/ WebSocket endpoint to expose it.

5. Tool scaffolding

Use templates/Tools.java.template. Tools are plain @ApplicationScoped CDI beans with @Tool-annotated methods the model may call. Wire them globally with @RegisterAiService(tools = TicketTools.class) or per method with @ToolBox(TicketTools.class). Tools run blocking by default; keep blocking I/O (DB, REST) off the event loop by annotating the method @RunOnVirtualThread. Validate a tool's arguments or results with tool-level guardrails — see §10.

6. MCP client scaffolding (consume remote MCP tools)

Use templates/McpClient.java.template. An AI service can take its tools from one or more MCP servers: annotate the service method with @McpToolBox("name") (io.quarkiverse.langchain4j.mcp.runtime) — or @McpToolBox with no name to activate every configured client — and declare each named client in application.properties (quarkus.langchain4j.mcp.<name>.transport-type + .url; prefer streamable-http, or stdio + .command for a local subprocess server). Requires the langchain4j-mcp extension (the platform BOM manages its version). Local @Tool beans (§5) and MCP toolboxes combine freely on the same service. Each client adds a readiness health check; disable with quarkus.langchain4j.mcp.health.enabled=false when the remote server is optional at startup.

7. MCP server scaffolding (expose your app as an MCP server)

Use templates/McpServer.java.template. Annotate business methods with @Tool / @ToolArg from io.quarkiverse.mcp.server (plus @Prompt / @Resource for reusable prompts and data) to offer them to any MCP client over Streamable HTTP at /mcp (quarkus.mcp.server.http.root-path). Requires the mcp-server-http extension (io.quarkiverse.mcp, managed by the platform's quarkus-mcp-server-bom — no version pin); use mcp-server-stdio instead when a desktop client spawns the app as a subprocess. Do not confuse the two @Tool annotations: io.quarkiverse.mcp.server.Tool offers a method to remote MCP clients, while dev.langchain4j.agent.tool.Tool (§5) offers it to your own model — the template delegates to the TicketTools bean so one implementation backs both. Enable quarkus.mcp.server.traffic-logging.enabled=true to watch the JSON-RPC exchanges in dev.

8. Agent scaffolding

Use templates/Agent.java.template. It shows the full declarative agentic shape:

• individual @Agent AI services (sub-agents) returning records;
• an orchestrator interface using @SequenceAgent / @ParallelAgent (and the @SupervisorAgent + @SupervisorRequest variant for routing) with @Output assembling the result from the AgenticScope;
• an @ApplicationScoped streaming bridge that runs the blocking workflow on a virtual thread and emits progress over a Mutiny Multi;
• the @WebSocket endpoint that delegates to the bridge.

Requires the quarkus-langchain4j-agentic extension. Call quarkus_skills for it before writing the workflow.

9. RAG pipeline scaffolding

Use templates/RagSetup.java.template. Default to Easy RAG: add quarkus-langchain4j-easy-rag plus an in-process embedding model (langchain4j-embeddings-all-minilm-l6-v2), drop documents into the folder referenced by quarkus.langchain4j.easy-rag.path, and let Quarkus ingest them on startup — no retriever code required. The template also includes a commented, opt-in manual path (a CDI-produced EmbeddingStore + EmbeddingStoreContentRetriever + RetrievalAugmentor) to use only when a project needs control Easy RAG does not provide.

10. Guardrails

Use templates/Guardrails.java.template. Guardrails are @ApplicationScoped CDI beans that validate an AI service's inputs (InputGuardrail) and outputs (OutputGuardrail); attach them with @InputGuardrails(…) / @OutputGuardrails(…) on the AI-service method or interface. Use the upstream dev.langchain4j.guardrail API — the Quarkus-specific guardrail API was removed. An output guardrail can force the model to answer again with reprompt(…); cap attempts with quarkus.langchain4j.guardrails.max-retries (default 3, 0 disables).

11. application.properties baseline

Use templates/application.properties.template — this baseline is owned by the skill, not generated by quarkus_create. It configures the Ollama provider with a local default model (cloud models shown as comments), a named smaller model for cheap subtasks, generous timeouts, request/response logging, disabled Dev Services, and the Easy RAG documents path. A commented MCP client block declares the named ops client used in §6. A commented MCP server block sets the Streamable HTTP path and traffic logging for §7. A commented observability block wires OTLP trace export and dev-only prompt/completion capture.

12. After scaffolding

quarkus_create already started dev mode, so verify through the Quarkus Agents MCP — never invoke Maven or Gradle directly. Run the tests with quarkus_callTool devui-testing_runTests, and inspect failures with quarkus_callTool devui-exceptions_getLastException (fall back to quarkus_logs for broader context). Keep the §13 wiring smoke test green.

To audit or bring an existing project in line with these conventions later, /audit-project runs a read-only conformance check and hands any fixes back to this skill's component sections.

13. Test scaffolding

Use templates/AiServiceTest.java.template. Its active content is a @QuarkusTest wiring smoke test (ChatAssistantTest) that injects the ChatAssistant AI service and asserts it is non-null: booting Quarkus builds the CDI container and the AI-service proxy, so a green test proves wiring and augmentation succeeded without calling the model and without a running Ollama — only quarkus-junit is needed. The template also carries commented, opt-in examples: a model-dependent test (live Ollama, temperature=0) and an AI-quality evaluation example (Scorer / @EvaluationTest with semantic-similarity or AI-judge strategies), backed by quarkus-langchain4j-testing-evaluation-junit5 — already listed, test-scoped, in templates/pom.xml.template (the platform BOM manages its version).

14. Cross-reference

For coding conventions to apply once scaffolding is done — Java language level, virtual threads, records/sealed/pattern matching, declarative AI services, streaming, RAG, testing — see the project's CLAUDE.md (Claude) or AGENTS.md (Codex). This skill does not duplicate those conventions.