feat(ux): fix focus swipe animation, button visibility and mobile scroll

_bmad/bmb/workflows/workflow/data/csv-data-file-standards.md

@@ -1,31 +1,20 @@
 # CSV Data File Standards
 
-**Purpose:** When workflows need structured data that LLMs cannot generate.
-
----
-
 ## When to Use CSV
 
-Use CSV for data that is:
-- Domain-specific and not in training data
+Use for:
+- Domain-specific data not in training data
 - Too large for prompt context
-- Needs structured lookup/reference
-- Must be consistent across sessions
+- Structured lookup/reference needs
+- Cross-session consistency required
 
-**Don't use for:**
-- Web-searchable information
-- Common programming syntax
-- General knowledge
-- Things LLMs can generate
-
----
+**Don't use for:** Web-searchable info, common syntax, general knowledge, LLM-generatable content
 
 ## CSV Structure
 
 ```csv
 category,name,pattern,description
 "collaboration","Think Aloud Protocol","user speaks thoughts → facilitator captures","Make thinking visible during work"
-"creative","SCAMPER","substitute→combine→adapt→modify→put→eliminate→reverse","Systematic creative thinking"
 ```
 
 **Rules:**
@@ -34,48 +23,31 @@ category,name,pattern,description
 - UTF-8 encoding
 - All columns must be used in workflow
 
----
-
 ## Common Use Cases
 
-### 1. Method Registry
-Advanced Elicitation uses CSV to select techniques dynamically:
+### Method Registry
 ```csv
 category,name,pattern
 collaboration,Think Aloud,user speaks thoughts → facilitator captures
 advanced,Six Thinking Hats,view problem from 6 perspectives
 ```
 
-### 2. Knowledge Base Index
-Map keywords to document locations for surgical lookup:
+### Knowledge Base Index
 ```csv
 keywords,document_path,section
 "nutrition,macros",data/nutrition-reference.md,## Daily Targets
 ```
 
-### 3. Configuration Lookup
-Map scenarios to parameters:
+### Configuration Lookup
 ```csv
 scenario,required_steps,output_sections
 "2D Platformer",step-01,step-03,step-07,movement,physics,collision
 ```
 
----
-
 ## Best Practices
 
-- Keep files small (<1MB if possible)
+- Keep files small (<1MB preferred)
 - No unused columns
-- Document each CSV's purpose
-- Validate data quality
 - Use efficient encoding (codes vs full descriptions)
-
----
-
-## Validation Checklist
-
-For each CSV file:
-- [ ] Purpose is essential (can't be generated by LLM)
-- [ ] All columns are used somewhere
-- [ ] Properly formatted (consistent, UTF-8)
-- [ ] Documented with examples
+- Document purpose
+- Validate data quality