# Examples: langgraph-explainable-agent

## Usage Example

```python
# How to use this skill
# Inputs: user_query - text input from the user, context_documentation - pre-indexed documents for retrieval, knowledge_graph - graph database for entity relationships
# Process: Step 1: Create LangGraph chain with agent that processes user query through knowledge graph retrieval and citation generation → Step 2: Execute the chain to generate explainable answer with block citations → Step 3: Apply permission-aware filtering on retrieved context before final answer
# Outputs: explainable_answer_with_citations - final response with source references, actionable_results - structured output for downstream tasks
```