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-node-configuration/OPERATION_PATTERNS.md

@@ -22,7 +22,7 @@ Common node configuration patterns organized by node type and operation.
 
 ### HTTP Request (nodes-base.httpRequest)
 
-Most versatile node - 892 templates use this!
+Most versatile node for HTTP operations
 
 #### GET Request
 
@@ -229,7 +229,7 @@ Most common trigger - 813 searches!
 
 ### Slack (nodes-base.slack)
 
-Second most popular - 234 AI agent templates use this!
+Popular choice for AI agent workflows
 
 #### Post Message
 

skills/n8n-node-configuration/README.md

@@ -10,12 +10,11 @@ Expert guidance for operation-aware node configuration with property dependencie
 
 ## The Problem This Solves
 
-From analysis of 447,557 MCP tool usage events:
+Node configuration patterns:
 
-- **38,287 workflow updates** (node configurations)
-- **9,835 get_node_essentials calls** (18s avg from search → essentials)
-- **91.7% success rate** with essentials-based configuration
-- **56 seconds average** between configuration edits
+- get_node_essentials is the primary discovery tool (18s avg from search → essentials)
+- 91.7% success rate with essentials-based configuration
+- 56 seconds average between configuration edits
 
 **Key insight**: Most configurations only need essentials, not full schema!
 
@@ -105,21 +104,20 @@ n8n-node-configuration/
 
 ## Usage Statistics
 
-From telemetry analysis:
+Configuration metrics:
 
 | Metric | Value | Insight |
 |---|---|---|
-| Total workflow updates | 38,287 | High configuration activity |
-| get_node_essentials calls | 9,835 | Most popular discovery pattern |
+| get_node_essentials | Primary tool | Most popular discovery pattern |
 | Success rate (essentials) | 91.7% | Essentials sufficient for most |
 | Avg time search→essentials | 18 seconds | Fast discovery workflow |
 | Avg time between edits | 56 seconds | Iterative configuration |
 
 ## Tool Usage Pattern
 
-**Most common discovery pattern** (9,835 occurrences):
+**Most common discovery pattern**:
 ```
-search_nodes → get_node_essentials (18s avg)
+search_nodes → get_node_essentials (18s average)
 ```
 
 **Configuration cycle**:

skills/n8n-node-configuration/SKILL.md

@@ -13,9 +13,8 @@ Expert guidance for operation-aware node configuration with property dependencie
 
 **Progressive disclosure**: Start minimal, add complexity as needed
 
-From telemetry analysis:
-- 38,287 workflow updates (node configurations)
-- 9,835 get_node_essentials calls (most used discovery pattern)
+Configuration best practices:
+- get_node_essentials is the most used discovery pattern
 - 56 seconds average between configuration edits
 - 91.7% success rate with essentials-based configuration