Agent skill

Langchain4j AI Services Patterns

by giuseppe-trisciuoglio in giuseppe-trisciuoglio/developer-kit

Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java.

MITAuto-check: notesAI & LLM Engineering

Install Langchain4j AI Services Patterns

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .claude/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .claude/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .agents/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .agents/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .cursor/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .cursor/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/giuseppe-trisciuoglio/developer-kit.git --path plugins/developer-kit-java/skills/langchain4j-ai-services-patterns

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .gemini/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .gemini/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .github/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .github/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install giuseppe-trisciuoglio/developer-kit langchain4j-ai-services-patterns --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns .opencode/skills/langchain4j-ai-services-patterns && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "langchain4j-ai-services-patterns" agent skill from https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/langchain4j-ai-services-patterns into .opencode/skills/langchain4j-ai-services-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain4j-ai-services-patterns", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: langchain4j-ai-services-patterns
GitHub stars: 357
Token cost: ~1.6k tokens
SKILL.md length: 423 words
Files: 3 (incl. references)
Skills in repo: 115
Repo updated: Sep 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java.

Works in 6 steps: Define AI Service Interface → Add Annotations for System and User… → Create AI Service Instance → …
Creating AI-powered Java applications with minimal boilerplate
SKILL.md covers Overview, When to Use, Instructions and Examples, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Langchain4j AI Services Patterns is an agent skill from giuseppe-trisciuoglio/developer-kit. Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/examples.md` and `references/references.md`).

It sits in AI & LLM Engineering, covering Structured output and tool calling, Chatbots and conversational support and Type safety. It works with Java. The repository describes itself as: Modular plugin marketplace for Claude Code and agentic CLIs, with validated, spec-driven skills, agents, commands, and workflows for Java, TypeScript, Python, PHP, AWS, and AI. The licence is MIT.

When your agent uses it

Creating AI-powered Java applications with minimal boilerplate
Implementing conversational AI with memory
Building AI agents with function calling

Example prompts

“Use the langchain4j-ai-services-patterns skill to provide patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot…”
“/langchain4j-ai-services-patterns”

Requirements

Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep

Workflow steps

6 steps, taken from the step headings in SKILL.md.

Define AI Service Interface
Add Annotations for System and User Messages
Create AI Service Instance
Configure Memory for Multi-turn Conversations
Integrate Tools for Function Calling
Validate and Test

What it can do on your machine

Read from SKILL.md and the folder at commit fe73fb3. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are java, xml and gradle).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- langchain4j.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Langchain4j AI Services Patterns loads about 1.6k tokens when it runs, and up to ~9k if it reads all its reference files. Until then it costs about 120 tokens; SKILL.md has 423 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~120
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Read, Write, Edit, Bash, Glob, Grep
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from giuseppe-trisciuoglio/developer-kit at commit fe73fb3, republished under its MIT licence (© giuseppe-trisciuoglio). 423 words, ~1,601 tokens.

Download SKILL.mdSave it as .claude/skills/langchain4j-ai-services-patterns/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.

name: langchain4j-ai-services-patterns
description: Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.
allowed-tools: Read, Write, Edit, Bash, Glob, Grep

LangChain4j AI Services Patterns

This skill provides guidance for building declarative AI Services with LangChain4j using interface-based patterns, annotations for system and user messages, memory management, tools integration, and advanced AI application patterns that abstract away low-level LLM interactions.

Overview

LangChain4j AI Services define AI functionality using Java interfaces with annotations, providing type-safe, declarative AI with minimal boilerplate.

When to Use

Use this skill when:

Building declarative AI services with minimal boilerplate using Java interfaces
Creating type-safe conversational AI with memory management
Implementing AI agents with function/tool calling capabilities
Designing AI services returning structured data (enums, POJOs, lists)
Integrating RAG patterns declaratively

Instructions

Follow these steps to create declarative AI Services with LangChain4j:

1. Define AI Service Interface

Create a Java interface with method signatures for AI interactions:

java

interface Assistant {
    String chat(String userMessage);
}

2. Add Annotations for System and User Messages

Use @SystemMessage and @UserMessage annotations to define prompts:

java

interface CustomerSupportBot {
    @SystemMessage("You are a helpful customer support agent for TechCorp")
    String handleInquiry(String customerMessage);

    @UserMessage("Analyze sentiment: {{it}}")
    Sentiment analyzeSentiment(String feedback);
}

3. Create AI Service Instance

Use AiServices builder or create to instantiate the service:

java

// Simple creation
Assistant assistant = AiServices.create(Assistant.class, chatModel);

// Or with builder for advanced configuration
Assistant assistant = AiServices.builder(Assistant.class)
    .chatModel(chatModel)
    .build();

4. Configure Memory for Multi-turn Conversations

Add memory management using @MemoryId for multi-user scenarios:

java

interface MultiUserAssistant {
    String chat(@MemoryId String userId, String userMessage);
}

Assistant assistant = AiServices.builder(MultiUserAssistant.class)
    .chatModel(model)
    .chatMemoryProvider(userId -> MessageWindowChatMemory.withMaxMessages(10))
    .build();

5. Integrate Tools for Function Calling

java

class Calculator {
    @Tool("Add two numbers") double add(double a, double b) { return a + b; }
}

interface MathGenius {
    String ask(String question);
}

MathGenius mathGenius = AiServices.builder(MathGenius.class)
    .chatModel(model)
    .tools(new Calculator())
    .build();

6. Validate and Test

Test AI services with concrete validation patterns:

java

// 1. Test with sample inputs
String response = assistant.chat("Hello, how are you?");
assert response != null && !response.isEmpty();

// 2. Validate structured outputs with assertions
Sentiment result = bot.analyzeSentiment("Great product!");
assert result == Sentiment.POSITIVE;

// 3. Log tool calls with side effects for audit
MathGenius math = AiServices.builder(MathGenius.class)
    .chatModel(model)
    .tools(new Calculator())
    .build();

// 4. Test memory isolation between users
String userA = assistant.chat("User A message", "session-a");
String userB = assistant.chat("User B message", "session-b");
assert !userA.equals(userB); // Verify memory isolation

Examples

See examples.md for comprehensive practical examples including:

Basic chat interfaces
Stateful assistants with memory
Multi-user scenarios
Structured output extraction
Tool calling and function execution
Streaming responses
Error handling
RAG integration
Production patterns

API Reference

Complete API documentation, annotations, interfaces, and configuration patterns are available in references.md.

Show full SKILL.md (177 more words)Show less

Best Practices

Use type-safe interfaces instead of string-based prompts
Implement proper memory management with appropriate limits
Design clear tool descriptions with parameter documentation
Handle errors gracefully with custom error handlers
Use structured output for predictable responses
Implement validation for user inputs
Monitor performance for production deployments

Dependencies

xml

<!-- Maven -->
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j</artifactId>
    <version>1.8.0</version>
</dependency>
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-open-ai</artifactId>
    <version>1.8.0</version>
</dependency>

gradle

// Gradle
implementation 'dev.langchain4j:langchain4j:1.8.0'
implementation 'dev.langchain4j:langchain4j-open-ai:1.8.0'

References

Constraints and Warnings

AI Services rely on LLM responses which are non-deterministic; tests should account for variability.
Memory providers store conversation history; ensure proper cleanup for multi-user scenarios.
Tool execution can be expensive; implement rate limiting and timeout handling.
Never pass sensitive data (API keys, passwords) in system or user messages.
Large context windows can lead to high token costs; implement message pruning strategies.
Streaming responses require proper error handling for partial failures.
AI-generated outputs should be validated before use in production systems.
Be cautious with tools that have side effects; AI models may call them unexpectedly.
Token limits vary by model; ensure prompts and context fit within model constraints.

Files

SKILL.md and 2 other files (references) in plugins/developer-kit-java/skills/langchain4j-ai-services-patterns of giuseppe-trisciuoglio/developer-kit.

SKILL.md
references/examples.md
references/references.md

Open the folder on GitHubat commit fe73fb3

Compare with similar skills

Langchain4j AI Services Patterns next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Langchain4j AI Services Patterns compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Langchain4j AI Services Patterns this skillgiuseppe-trisciuoglio/developer-kit	357	—	~1.6k	Automated safety check: Notes	MIT	1 mo ago
Google Agents CLI Adk Codepifferologo/cloud-agents-cli	129	1 repos	~768	Automated safety check: Pass	Apache-2.0	1 mo ago
AI SDKvercel-labs/ai-facts	168	20 repos	~1.2k	Automated safety check: Pass	None	5 mo ago
LangchainOrchestra-Research/AI-Research-SKILLs	13k	2 repos	~3.2k	Automated safety check: Pass	MIT	3 mo ago
Sap Cloud SDK AIsecondsky/sap-skills	462	—	~3.2k	Automated safety check: Pass	GPL-3.0	5 days ago
Scaffolding Openai Agentsaiskillstore/marketplace	433	—	~3.3k	Automated safety check: Pass	None	yesterday

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Works with

Java

Questions about Langchain4j AI Services Patterns

What does Langchain4j AI Services Patterns do?

Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Langchain4j AI Services Patterns is an agent skill from giuseppe-trisciuoglio/developer-kit. Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java.

When should I use Langchain4j AI Services Patterns?

Langchain4j AI Services Patterns fits situations like: creating AI-powered Java applications with minimal boilerplate; implementing conversational AI with memory; building AI agents with function calling.

How do I install Langchain4j AI Services Patterns in Claude Code?

Run `npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a claude-code`. Or copy the skill folder (plugins/developer-kit-java/skills/langchain4j-ai-services-patterns in giuseppe-trisciuoglio/developer-kit) into .claude/skills/langchain4j-ai-services-patterns in your project. Claude Code loads it when a task matches its description.

How do I install Langchain4j AI Services Patterns in Codex?

Run `npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a codex`. Or copy the skill folder (plugins/developer-kit-java/skills/langchain4j-ai-services-patterns in giuseppe-trisciuoglio/developer-kit) into .agents/skills/langchain4j-ai-services-patterns in your project. Codex loads it when a task matches its description.

Can I use Langchain4j AI Services Patterns in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add giuseppe-trisciuoglio/developer-kit --skill langchain4j-ai-services-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langchain4j-ai-services-patterns, .gemini/skills/langchain4j-ai-services-patterns, .github/skills/langchain4j-ai-services-patterns and .opencode/skills/langchain4j-ai-services-patterns in your project.

What does Langchain4j AI Services Patterns need to run?

SKILL.md names no scripts, command-line tools or credentials: Langchain4j AI Services Patterns is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep.

Does Langchain4j AI Services Patterns access the network?

SKILL.md names 1 domain. As links in the text: langchain4j.com. This is read from the text; nothing was executed.

Is Langchain4j AI Services Patterns safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Langchain4j AI Services Patterns use?

Langchain4j AI Services Patterns is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Langchain4j AI Services Patterns use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.4k tokens, read only when the agent opens those files.

What are the alternatives to Langchain4j AI Services Patterns?

Skills that share tags, products or a category with Langchain4j AI Services Patterns: Google Agents CLI Adk Code (pifferologo/cloud-agents-cli, 129 stars), AI SDK (vercel-labs/ai-facts, 168 stars), Langchain (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Sap Cloud SDK AI (secondsky/sap-skills, 462 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Langchain4j AI Services Patterns?

giuseppe-trisciuoglio (a GitHub user) maintains it in giuseppe-trisciuoglio/developer-kit, which has 357 GitHub stars. The repository holds 115 skills in this directory. The repository was last updated on September 10, 2026.

Source: giuseppe-trisciuoglio/developer-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Langchain4j AI Services Patterns

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SKILL.md

LangChain4j AI Services Patterns

Overview

When to Use

Instructions

1. Define AI Service Interface

2. Add Annotations for System and User Messages

3. Create AI Service Instance

4. Configure Memory for Multi-turn Conversations

5. Integrate Tools for Function Calling

6. Validate and Test

Examples

API Reference

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References

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