refactor: Remove research context from skill content

Cleaned up all skills to remove research/telemetry context that was used
during design but is not needed at runtime when AI agents use the skills.

## Changes Made

### Pattern 1: Research Framing Removed
- "From analysis of X workflows/events" → Removed
- "From telemetry analysis:" → Replaced with operational context
- "Based on X real workflows" → Simplified to general statements

### Pattern 2: Popularity Metrics Removed
- "**Popularity**: Second most common (892 templates)" → Removed entirely
- "813 searches", "456 templates", etc. → Removed

### Pattern 3: Frequency Percentages Converted
- "**Frequency**: 45% of errors" → "Most common error"
- "**Frequency**: 28%" → "Second most common"
- "**Frequency**: 12%" → "Common error"
- Percentages in tables → Priority levels (Highest/High/Medium/Low)

### Pattern 4: Operational Guidance Kept
- ✅ Success rates (91.7%) - helps tool selection
- ✅ Average times (18s, 56s) - sets expectations
- ✅ Relative priority (most common, typical) - guides decisions
- ✅ Iteration counts (2-3 cycles) - manages expectations

## Files Modified (19 files across 4 skills)

**Skill #2: MCP Tools Expert (5 files)**
- Removed telemetry occurrence counts
- Kept success rates and average times

**Skill #3: Workflow Patterns (7 files)**
- Removed all popularity metrics from pattern files
- Removed "From analysis of 31,917 workflows"
- Removed template counts

**Skill #4: Validation Expert (4 files)**
- Converted frequency % to priority levels
- Removed "From analysis of 19,113 errors"
- Removed telemetry loop counts (kept iteration guidance)

**Skill #5: Node Configuration (3 files)**
- Removed workflow update counts
- Removed essentials call counts
- Kept success rates and timing guidance

## Result

Skills now provide clean, focused runtime guidance without research
justification. Content is more actionable for AI agents using the skills.

All technical guidance, examples, patterns, and operational metrics preserved.
Only removed: research methodology, data source attribution, and statistical
justification for design decisions.

🤖 Conceived by Romuald Członkowski - https://www.aiadvisors.pl/en

skills/n8n-mcp-tools-expert/README.md

@@ -6,7 +6,7 @@ Expert guide for using n8n-mcp MCP tools effectively.
 
 ## Purpose
 
-Teaches how to use n8n-mcp MCP server tools correctly, fixing the 20% failure rate when using tools incorrectly.
+Teaches how to use n8n-mcp MCP server tools correctly for efficient workflow building.
 
 ## Activates On
 

skills/n8n-mcp-tools-expert/SEARCH_GUIDE.md

@@ -192,7 +192,7 @@ Step 4: Use in Workflow
 (Configuration ready!)
 ```
 
-**From telemetry**: search → essentials is most common pattern (9,835 occurrences, 18s avg)
+**Most common pattern**: search → essentials (18s average)
 
 ---
 

skills/n8n-mcp-tools-expert/SKILL.md

@@ -23,7 +23,7 @@ n8n-mcp provides **40+ tools** organized into categories:
 
 ## Quick Reference
 
-### Most Used Tools (by frequency & success rate)
+### Most Used Tools (by success rate)
 
 | Tool | Use When | Success Rate | Speed |
 |------|----------|--------------|-------|
@@ -58,7 +58,7 @@ get_node_essentials({nodeType: "nodes-base.slack"})
 // Returns: operations, properties, examples
 ```
 
-**Pattern from telemetry**: search → essentials (9,835 occurrences, 18s avg)
+**Common pattern**: search → essentials (18s average)
 
 ### Validating Configuration
 
@@ -69,7 +69,7 @@ get_node_essentials({nodeType: "nodes-base.slack"})
 3. [Repeat] Fix errors, validate again
 ```
 
-**Pattern from telemetry**: validate → fix → validate (7,841 loops, 23s thinking, 58s fixing)
+**Common pattern**: validate → fix → validate (23s thinking, 58s fixing per cycle)
 
 ### Managing Workflows
 
@@ -81,7 +81,7 @@ get_node_essentials({nodeType: "nodes-base.slack"})
 4. n8n_validate_workflow({id}) again
 ```
 
-**Pattern from telemetry**: update (38,287 uses, 56s avg between edits)
+**Common pattern**: iterative updates (56s average between edits)
 
 ---
 
@@ -250,7 +250,7 @@ n8n_update_partial_workflow({id, operations: [...]})
 
 ### Pattern 1: Node Discovery (Most Common)
 
-**From telemetry**: 9,835 occurrences, 18s avg between steps
+**Common workflow**: 18s average between steps
 
 ```javascript
 // Step 1: Search (fast!)
@@ -271,7 +271,7 @@ const details = await get_node_essentials({
 
 ### Pattern 2: Validation Loop
 
-**From telemetry**: 7,841 occurrences, 23s thinking, 58s fixing
+**Typical cycle**: 23s thinking, 58s fixing
 
 ```javascript
 // Step 1: Validate
@@ -298,7 +298,7 @@ await validate_node_operation({...});  // Repeat until clean
 
 ### Pattern 3: Workflow Editing
 
-**From telemetry**: 38,287 uses, 99.0% success, 56s avg between edits
+**Most used update tool**: 99.0% success rate, 56s average between edits
 
 ```javascript
 // Iterative workflow building (NOT one-shot!)

skills/n8n-mcp-tools-expert/VALIDATION_GUIDE.md

@@ -8,7 +8,7 @@ Complete guide for validating node configurations and workflows.
 
 **Validate early, validate often**
 
-From telemetry: 15,107 validation loops, 7,841 validate → fix cycles
+Validation is typically iterative with validate → fix cycles
 
 ---
 
@@ -156,7 +156,7 @@ validate_workflow({
 
 ## Validation Loop Pattern
 
-**From telemetry**: 7,841 occurrences, 23s thinking, 58s fixing
+**Typical cycle**: 23s thinking, 58s fixing
 
 ```
 1. Configure node

skills/n8n-mcp-tools-expert/WORKFLOW_GUIDE.md

@@ -81,7 +81,7 @@ n8n_create_workflow({
 
 **Use when**: Making incremental changes to workflows
 
-**Pattern from telemetry**: 56s avg between edits (iterative building!)
+**Common pattern**: 56s average between edits (iterative building!)
 
 ### 15 Operation Types