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 rrezartprebreza/spring-boot-skills --skill spring-ai-integrationgit clone --depth 1 https://github.com/rrezartprebreza/spring-boot-skillsWrote 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/rrezartprebreza/spring-boot-skills/spring-ai-integration)<a href="https://agentmods.dev/skills/rrezartprebreza/spring-boot-skills/spring-ai-integration"><img src="https://agentmods.dev/badge/skills/rrezartprebreza/spring-boot-skills/spring-ai-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/rrezartprebreza/spring-boot-skills/spring-ai-integration"><img src="https://agentmods.dev/badge/skills/rrezartprebreza/spring-boot-skills/spring-ai-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00066 | $0.01848 |
| Opus 5 | $0.00033 | $0.00924 |
| Sonnet 5 | $0.00013 | $0.00370 |
| Haiku 4.5 | $0.00007 | $0.00185 |
Grade A, and why
spring-ai-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 13d ago.
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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spring AI Integration
Dependencies
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>1.0.0</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<!-- Choose your model provider — 1.0 GA renamed every starter to spring-ai-starter-* -->
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-anthropic</artifactId>
</dependency>
<!-- OR -->
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-openai</artifactId>
</dependency>
<!-- For RAG / vector search -->
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-vector-store-pgvector</artifactId>
</dependency>
</dependencies>
Watch the artifact names. 1.0 GA dropped the old
spring-ai-<x>-spring-boot-startercoordinates. The pattern is nowspring-ai-starter-model-<provider>(e.g.-model-anthropic,-model-openai) andspring-ai-starter-vector-store-<store>. Agents trained on pre-GA Spring AI will emit the dead names — they resolve to nothing in Maven Central.
ChatClient — Basic Usage
@Service
@RequiredArgsConstructor
public class DocumentSummaryService {
private final ChatClient chatClient;
public String summarize(String conversationId, String content) {
return chatClient.prompt()
.advisors(a -> a.param(ChatMemory.CONVERSATION_ID, conversationId))
.user(u -> u.text("Summarize the following document in 3 bullet points:\n\n{content}")
.param("content", content))
.call()
.content();
}
// With system prompt
public String analyzeFinancial(String conversationId, String document, String language) {
return chatClient.prompt()
.advisors(a -> a.param(ChatMemory.CONVERSATION_ID, conversationId))
.system("You are a financial analyst. Respond in {language}.")
.system(s -> s.param("language", language))
.user(document)
.call()
.content();
}
}
What ships with it
5 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.
- 13d ago First seen · 261 lines · 66 tokens per session scan A 960d046a328c
spring-ai-integration is a skill published in the GitHub repository rrezartprebreza/spring-boot-skills (261 stars, last pushed 5d ago), licensed MIT. It adds 66 tokens to every session and 1,848 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
spring-ai
Spring AI for integrating AI/ML models (OpenAI, Azure, Ollama, etc.) into Spring applications. Covers ChatClient, embeddings, RAG, vector stores, and function calling. USE WHEN: user mentions "spring ai", "ChatClient", "LLM integration Spring", "RAG Spring", "embeddings Java", "vector store Spring", "OpenAI Spring…
astra-vector-backend
Design Astra DB Data API and vector-search backends for retrieval, metadata filtering, and LangChain-compatible stores.
mdc-langchain-rag-application-development
Applies specifically when developing RAG (Retrieval-Augmented Generation) applications using Langchain within Next.js projects.
java-spring-ai
Use when the user asks to add AI features, integrate Spring AI or LangChain4J, build a chatbot, implement RAG (retrieval-augmented generation), use vector stores, stream LLM responses, or call AI tools/functions in a Spring Boot project.
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…
azure-search-documents-ts
Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.