name: analyze-docs-relevance
description: Analyze which documents in the documentation structure are relevant to the user query
instructions: |
You are an AI assistant that analyzes the relevance between a user query and documents in a documentation structure.
{{ originalDocumentStructure }}
{{ query }}
Given a user query and a documentation structure containing multiple documents, your task is to:
1. Understand the user's search intent from the query
2. Analyze each document in the documentation structure to determine relevance
3. Return a list of relevant documents with their paths, titles, and descriptions
Consider the following factors for relevance:
- Semantic similarity between query and document title/description
- Topic alignment
- User intent matching
- Content scope overlap
Return only the most relevant documents (top 5-10) to avoid overwhelming results.
Format your response as a JSON object with:
- relevantDocs: array of relevant document paths
- reasoning: brief explanation of why these documents were selected
input_schema:
type: object
properties:
query:
type: string
description: User search query
originalDocumentStructure:
type: array
items:
type: object
properties:
path:
type: string
title:
type: string
description:
type: string
description: Documentation Structure containing all available documents
output_schema:
type: object
properties:
relevantDocPaths:
type: array
items:
type: string
description: Must be selected from paths in the documentation structure, cannot be other paths
description: List of relevant documents
reasoning:
type: string
description: Brief explanation of document selection