> ## Documentation Index > Fetch the complete documentation index at: https://docs.hipocap.com/llms.txt > Use this file to discover all available pages before exploring further. # Scoring with Hosted Evaluators ## Creating a Basic Online Evaluator This example walks through setting up a simple online evaluator that checks if an LLM response contains specific keywords, useful for content moderation or topic classification. From your Laminar dashboard, go to the Evaluators page and click "New Evaluator" to start creating your custom evaluation logic. Create a Python function that analyzes the LLM output. This example checks for the presence of specific keywords and assigns a score based on relevance. **Important**: Online evaluator functions must return a single number as the score. The system automatically attaches this score to the span for monitoring and analysis. ```python theme={null} def keyword_checker(input): """ Evaluator that checks if the output contains relevant keywords Returns a score from 0 to 1 based on keyword presence Note: Must return a single number as the score """ def extract_text(data): if isinstance(data, str): return data if isinstance(data, dict) and 'content' in data: content = data['content'] if isinstance(content, str): return content if isinstance(content, list) and content: first = content[0] return first.get('text', str(first)) if isinstance(first, dict) else str(first) return str(data) text_content = extract_text(input) important_keywords = ['solution', 'help', 'recommend', 'suggest'] keyword_count = sum(1 for keyword in important_keywords if keyword in text_content.lower()) return min(keyword_count / len(important_keywords), 1.0) ``` Create evaluator function Use the test interface to verify your evaluator works correctly with sample inputs. ```python theme={null} { "content": [ {"text": "Let me suggest a helpful approach"} ] } ``` Test evaluator Navigate to your traces, find a span representing the LLM call you want to evaluate, and register your evaluator to that specific span path by clicking evaluators on span view. Register to span path After registration, new spans on that path will automatically trigger your evaluator. Check the span details to see the attached evaluation scores. Verify execution - evaluator scores displayed in span