Morning catch-up view — assigned Jira tickets, open PRs, current working copy state, and (if present) in-progress and ready beads in one glance. Run at session start to orient.
Routet je Bundesland: Landeswahlgesetz, Landeswahlordnung, Wahlleiter, Fristen, Formulare und Aufstellungsanforderungen.
Landwirtschaftliche Erzeugerkooperation: prüft die einschlägigen Voraussetzungen, Dokumente, Risiken und Ausnahmen. Norm-/Quellenanker: Art.
Prüft Agrarroboter: Maschinenrecht, autonome Fahrt, Umweltrisiken, Pflanzenschutz, Daten, Betreiberpflichten und Versicherung. — from Klotzkette/claude-fuer-deutsches-recht
Prüft Agrarroboter: Maschinenrecht, autonome Fahrt, Umweltrisiken, Pflanzenschutz, Daten, Betreiberpflichten und Versicherung. — from Klotzkette/claude-fuer-deutsches-recht
Lane integration. Manage data, records, and automate workflows. Use when the user wants to interact with Lane data.
Full language coaching review for the current session
Foundational Carbon patterns covering memory safety, modern syntax, C++ interop, and Carbon idioms. Use when writing Carbon code or migrating from C++.
Foundational Clojure patterns covering functional programming, REPL-driven development, immutable data structures, and idiomatic code.
Foundational C++ patterns covering core syntax, classes, templates, RAII, move semantics, and modern C++ features (C++11/14/17/20).
Foundational Cypher (Neo4j) patterns covering graph pattern matching, MATCH/CREATE/MERGE/DELETE operations, relationships, path patterns, aggregation, filtering, and common graph…
Foundational Elixir patterns covering modules, pattern matching, processes, OTP behaviors (GenServer, Supervisor), Phoenix framework basics, and functional programming idioms.
Foundational Erlang patterns covering OTP behaviors, fault-tolerant systems, distributed computing, pattern matching, processes, and supervision trees.
Foundational F# patterns covering functional-first programming, type providers, computation expressions, and domain modeling.
Use when writing, auditing, or generating documentation for projects in unsupported languages — covers docstring conventions, API doc extraction, and generic heuristic patterns.
Foundational Go patterns covering types, interfaces, goroutines, channels, and common idioms. Use when writing Go code, understanding Go's concurrency model, or needing guidance…
Foundational Haskell patterns covering pure functional programming, type system, type classes, monads, and common idioms.
Foundational Objective-C patterns covering classes, protocols, categories, memory management (ARC/retain-release), blocks, GCD, and Foundation framework.
Build React SPAs where components are declarative UI consuming external state (Zustand/XState/TanStack Query). Logic lives in stores, not components.
Rust 1.92+ development specialist covering Axum, Tokio, SQLx, and memory-safe systems programming. Use when building high-performance, memory-safe applications or WebAsse — from…
Foundational Scala patterns covering immutability, pattern matching, traits, case classes, for-comprehensions, and functional programming.
Scala-specific library development patterns. Use when creating Scala libraries, designing public APIs with immutability, configuring sbt/Mill build tools, managing cross-Scala…
Foundational SPARQL patterns covering RDF querying, triple patterns, graph patterns, and semantic web fundamentals. Use when querying RDF data or working with knowledge graphs.
Automate Langbase tasks via Rube MCP (Composio). Always search tools first for current schemas. — from general/automation
Scaffold a basic LangChain/LangGraph ReAct agent with a tool, wired to any OpenAI-compatible endpoint.
Building LLM agents with LangChain and LangGraph, covering tool-calling model initialization, state management, and observability with LangSmith.
Guide to using ChatPromptTemplate and MessagesPlaceholder in LangChain for conversational AI. Use when building chatbots, conversational interfaces, or AI assistants that need to…
Diagnose and fix common LangChain errors and exceptions. Use when encountering LangChain import errors, auth failures, output parsing issues, agent loops, or version conflicts.
LangChain v0.3 ядро (import langchain). ТОЛЬКО при: create_agent, @tool decorator, init_chat_model, SystemMessage/HumanMessage/AIMessage, middleware before_model/after_model,…
Compose LangChain 1.0 chains with RunnableParallel, RunnableBranch, RunnablePassthrough.assign, and RunnableLambda — correct input/output shapes, debug probes, and typed…
Build LangChain LCEL chains with prompts, parsers, and composition. Use when creating prompt templates, building RunnableSequence pipelines, parallel/branching chains, or…
Build LangChain agents with tool calling for autonomous task execution. Use when creating AI agents, implementing tool/function calling, binding tools to models, or building…
Implement LangChain RAG pipelines with document loaders, text splitters, embeddings, and vector stores (Chroma, Pinecone, FAISS).
Build a LangGraph 1.0 Deep Agent — planner + subagents + virtual filesystem + reflection loop — without the state-growth and prompt-inheritance traps.
Build and query vector stores with LangChain 1.0 without getting burned by flipped score semantics, embedding-dim mismatches, reranker quirks, and chunk-splitter bugs.
Implement role-based access control for LangChain applications with multi-tenant isolation, model access control, and usage quotas.
Build reproducible evaluation pipelines for LangChain 1.0 chains and LangGraph 1.0 agents — golden datasets, LangSmith evaluate(), ragas RAG metrics, deepeval LLM-as-judge, agent…
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
Incident response procedures for LangChain production issues: provider outages, high error rates, latency spikes, and cost overruns.
LangChain v0.3 интеграции (import langchain-openai/langchain-anthropic). ТОЛЬКО при: Chroma/FAISS/Pinecone/Qdrant langchain, OpenAIEmbeddings, ChatOpenAI, ChatAnthropic,…
Build a correct LangGraph 1.0 ReAct agent with `create_react_agent` — typed tools, error propagation, recursion caps, and stop conditions that actually stop.
Build a correct LangGraph 1.0 StateGraph — typed TypedDict state with reducers, nodes, edges, compile, and recursion budgets — without hitting the silent-termination and…
Initialize and use LangChain chat models - includes provider selection (OpenAI, Anthropic, Google), model configuration, and invocation patterns
Configure LangChain across dev/staging/production environments with isolated API keys, environment-specific settings, and secrets.
Set up comprehensive observability for LangChain applications with LangSmith tracing, OpenTelemetry, Prometheus metrics, and alerts.
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
Wire LangChain 1.0 / LangGraph 1.0 traces into an OpenTelemetry-native backend (Jaeger, Honeycomb, Grafana Tempo, Datadog) with LLM-specific SLOs, safe prompt-content policy, and…
Building LLM applications with LangChain - chains, agents, RAG, memory, and production patterns for AI-powered apps.
Build Retrieval Augmented Generation (RAG) systems with LangChain - includes embeddings, vector stores, retrievers, document loaders, and text splitting
Create Obsidian clipping notes via Obsidian CLI using path pattern `{folder}/YYYY-MM-DD {title}.md`, with optional LLM-selected configured subfolders, auto-extract frontmatter…
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt…
Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI…
Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents.
Complete guide for building agents and workflows in LangConfig. Use when users need help configuring nodes, connecting agents, setting up tools, or designing multi-agent systems…
Langflow is an open-source visual builder for AI agents and workflows. It lets teams design flows graphically, expose them as APIs or MCP tools, and connect major LLMs, vector…
Instrument arifOS constitutional AI kernel with Langfuse LLM tracing. Use when (1) adding Langfuse tracing to arifOS tool calls, (2) wiring arifOS telemetry to Langfuse cloud or…
Execute Langfuse primary workflow: Tracing LLM calls and spans. Use when implementing LLM tracing, building traced AI features, or adding observability to existing LLM…
Monitor and optimize LLM costs using Langfuse analytics and dashboards. Use when tracking LLM spending, identifying cost anomalies, or implementing cost controls for AI…
Automates Langfuse Cloud dashboard interactions using Playwright MCP. Captures screenshots for documentation, extracts metrics for monitoring, navigates trace details for…
Manage Langfuse data export, retention, and compliance requirements. Use when exporting trace data, configuring retention policies, or implementing data compliance for LLM…