langgraph-implementation
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
npx skills add majiayu000/claude-skill-registry --skill langgraph-implementation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LangGraph Implementation ## Core Concepts LangGraph builds stateful, multi-actor agent applications using a graph-based architecture: - **StateGraph**: Builder class for defining graphs with shared state - **Nodes**: Functions that read state and return partial updates - **Edges**: Define execution flow (static or conditional) - **Channels**: Internal state management (LastValue, BinaryOperatorAggregate) - **Checkpointer**: Persistence for pause/resume capabilities ## Essential Imports ```python from langgraph.graph import StateGraph, START, END from langgraph.graph.message import MessagesState, add_messages from langgraph.checkpoint.memory import InMemorySaver from langgraph.types import Command, Send, interrupt, RetryPolicy from typing import Annotated from typing_extensions import TypedDict ``` ## State Schema Patterns ### Basic State with TypedDict ```python class State(TypedDict): counter: int # LastValue - stores last value messages: Annotated[list, operator.add] # Reducer - appends lists items: Annotated[list, lambda a, b: a + [b] if b else a] # Custom reducer ``` ### MessagesState for Chat Applications ```python from langgraph.graph.message import MessagesState class Stat
- Core Concepts
- Essential Imports
- State Schema Patterns
- Basic State with TypedDict
- MessagesState for Chat Applications
- Pydantic State (for validation)
- Building Graphs
- Basic Pattern
- Node Function Signature
- Conditional Edges
- Command Pattern (Dynamic Routing + State Update)
- Send Pattern (Fan-out/Map-Reduce)
- Checkpointing
- Enable Persistence
What does the langgraph-implementation skill do?
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langgraph-implementation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.