Langchain4j Tool Function Calling Patterns

Provides LangChain4j patterns for implementing MCP (Model Context Protocol) servers, creating Java AI tools, exposing tool calling capabilities, and integrating MCP clients with AI services. Use when building a Java MCP server, implementing tool calling in Java, connecting LangChain4j to external MCP servers, or securing tool exposure for agent workflows.

Query-driven targeted ingest from a specific AI agent's raw history. Use this skill when the user invokes /wiki-claude, /wiki-codex, /wiki-hermes, /wiki-openclaw, /wiki-copilot, /wiki-pi — with or without a search topic. Different from wiki-history-ingest (which bulk-ingests everything new): this skill finds sessions about a SPECIFIC TOPIC in a specific agent's history and ingests just those, then returns a synthesized answer immediately usable in the current session. Primary use case: you're working in agent A and want to pull in how you solved X in agent B's history. Cross-referencing, not archiving. Also trigger on: "what did I work on in codex about X", "search my claude sessions for Y", "pull in hermes knowledge about Z", "find that conversation where I did X in codex".

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

Provides SonarQube and SonarCloud integration patterns via the Model Context Protocol (MCP) server. Enables quality gate monitoring, issue discovery and triaging, pre-push code analysis, and rule education directly in the agent workflow. Use when the user wants to check quality gates, search for Sonar issues, analyze code snippets before committing, or understand SonarQube rules. Triggers on "sonarqube", "sonarcloud", "quality gate", "sonar issues", "analyze with sonar", "check sonar", "sonar rule", "pre-push analysis".

Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.