Update from source repository (workflow run: 19518670579) (PR #15561) (commit: 75c77fb980043e096b1a7d638be7fc6f0fd15ba8) (branch: 10.15.0.cl)

Author: GitHub Action Sync Bot

cloud/modules/ROOT/pages/spotter-model.adoc

@@ -105,10 +105,22 @@ Unless required for performance, we suggest avoiding having such columns and rel
 
 
 Adding clear and concise column descriptions improves Spotter’s accuracy by helping it interpret the column’s meaning, values, and intended use in queries.
+They serve as human-readable explanations helping end-users understand what each column represents.
 
+We recommend the following workflow:
+
+. Write clear, user-focused column descriptions.
+. Generate AI Context. This feature uses your descriptions, column names, and values.
+. Review and refine the AI Context with AI-specific instructions.
+
+Column descriptions versus AI Context:: Column descriptions are written for end users. They answer questions about what the data represents. Spotter uses column descriptions to understand basic column meaning when AI Context is absent.
++
+AI Context is for the AI. It provides permanent instruction to Spotter. Use AI Context for advanced logic, business rules, column prioritization, or special value interpretation.
+
+Focus on end users:: Write column descriptions for someone unfamiliar with your data model.
 
 Provide meaningful descriptions to improve query interpretation::
-Include a brief but informative description to clarify what the column represents. This helps Spotter generate more accurate responses.
+Include a brief but informative column description to clarify what the column represents. This helps Spotter generate more accurate responses.
 Example;; A column labeled "ACV" can have the description:
 "Annual Contract Value, representing total revenue from contracts over a year."
 This ensures Spotter correctly interprets queries related to revenue and ACV.
@@ -130,8 +142,8 @@ Example;; A column with Boolean values can have the description:
 This prevents misinterpretation of TRUE/FALSE values in queries.
 
 
-Keep descriptions concise (maximum 200 characters)::
-Spotter will only consider the first 200 characters of the description.
+Keep descriptions concise (maximum 400 characters)::
+Spotter considers up to 400 characters, but aim for around 200 characters for optimal AI Context generation.
 Ensure critical details are included within this limit for accurate interpretation.