Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-spring-boot-integrationgit clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration)<a href="https://agentmods.dev/skills/giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration"><img src="https://agentmods.dev/badge/skills/giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration"><img src="https://agentmods.dev/badge/skills/giuseppe-trisciuoglio/developer-kit/langchain4j-spring-boot-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00088 | $0.01938 |
| Opus 5 | $0.00044 | $0.00969 |
| Sonnet 5 | $0.00018 | $0.00388 |
| Haiku 4.5 | $0.00009 | $0.00194 |
Grade A, and why
langchain4j-spring-boot-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LangChain4j Spring Boot Integration
Integrate LangChain4j with Spring Boot using declarative AI Services, auto-configuration, and Spring Boot starters. Configure AI model beans, set up chat memory, implement RAG pipelines with Spring Data, and build production-ready AI applications.
When to Use
Use this skill when:
- Integrating LangChain4j into existing Spring Boot applications
- Building AI-powered microservices with Spring Boot
- Configuring AI model beans with
@Beanannotations - Setting up auto-configuration for AI models and services
- Creating declarative AI Services with Spring dependency injection
- Implementing RAG systems with Spring Data integrations
- Setting up chat memory with Spring context management
- Configuring multiple AI providers (OpenAI, Azure, Ollama, Anthropic)
- Building production-ready AI applications with Spring Boot
Overview
LangChain4j Spring Boot integration provides declarative AI Services through Spring Boot starters, enabling automatic configuration of AI components based on properties. Combine Spring dependency injection with LangChain4j's AI capabilities using interface-based definitions with annotations.
Instructions
1. Add Dependencies
<!-- Core LangChain4j Spring Boot Starter -->
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-spring-boot-starter</artifactId>
<version>1.8.0</version>
</dependency>
<!-- OpenAI Spring Boot Starter -->
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
<version>1.8.0</version>
</dependency>
2. Configure Application Properties
# application.properties
langchain4j.open-ai.chat-model.api-key=${OPENAI_API_KEY}
langchain4j.open-ai.chat-model.model-name=gpt-4o-mini
langchain4j.open-ai.chat-model.temperature=0.7
langchain4j.open-ai.chat-model.timeout=PT60S
langchain4j.open-ai.chat-model.max-tokens=1000
Or using YAML:
langchain4j:
open-ai:
chat-model:
api-key: ${OPENAI_API_KEY}
model-name: gpt-4o-mini
temperature: 0.7
timeout: 60s
max-tokens: 1000
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 306 lines · 88 tokens per session scan A e3a8351125ca
langchain4j-spring-boot-integration is a skill published in the GitHub repository giuseppe-trisciuoglio/developer-kit (343 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 1,938 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.
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