feedback

name	feedback
description	Collect content feedback and identify patterns for rule updates

Feedback Skill

Overview

Simple feedback system for content quality. Collect ratings, identify patterns, and get recommendations for rule updates.

Philosophy: Lightweight pattern identification → Manual rule improvements

---

Operations

rate - Collect feedback on content quality

• Entry: feedback-skill rate <path>
• Collects: Rating (1-5), issue category, optional comment
• Output: Stores in .kurt/kurt.sqlite
• Subskill: subskills/rate.md

dashboard - View feedback trends and summary

• Entry: feedback-skill dashboard [--days <n>]
• Shows: Overall stats, issue breakdown, rating trends, recent feedback
• Output: Console summary
• Subskill: subskills/dashboard.md

patterns - Identify recurring issues and recommend updates

• Entry: feedback-skill patterns [--days <n>] [--min-frequency <n>]
• Shows: Issues that occur ≥3 times with recommendations
• Output: Recommended writing-rules-skill commands
• Subskill: subskills/patterns.md

---

Routing Logic

Parse arguments → Route to subskill:

OPERATION=$1
shift

case "$OPERATION" in
    "rate")
        .claude/skills/feedback-skill/subskills/rate.md "$@"
        ;;

    "dashboard")
        .claude/skills/feedback-skill/subskills/dashboard.md "$@"
        ;;

    "patterns")
        .claude/skills/feedback-skill/subskills/patterns.md "$@"
        ;;

    *)
        echo "Unknown operation: $OPERATION"
        echo ""
        echo "Available operations:"
        echo "  rate       - Rate content quality"
        echo "  dashboard  - View feedback trends"
        echo "  patterns   - Identify recurring issues"
        exit 1
        ;;
esac

---

Data Storage

SQLite (.kurt/kurt.sqlite)

feedback_events (simplified schema)

CREATE TABLE feedback_events (
    id TEXT PRIMARY KEY,           -- UUID
    created_at TEXT NOT NULL,      -- ISO 8601 timestamp
    rating INTEGER NOT NULL,       -- 1-5
    comment TEXT,                  -- Optional text feedback
    issue_category TEXT,           -- tone|structure|info|comprehension|length|examples|other
    asset_path TEXT,               -- Path to rated content
    project_id TEXT                -- Optional project context
);

Removed tables (from previous complex version):

• improvements - No automated execution tracking
• workflow_retrospectives - Workflows removed
• workflow_phase_ratings - Workflows removed
• feedback_loops - Too complex for simple system

---

Simple Feedback Flow

1. User creates content

2. User rates content (optional):
   feedback-skill rate <path>
   → Rating: 1-5
   → Issue category (if ≤3)
   → Optional comment

3. View trends over time:
   feedback-skill dashboard
   → Overall stats
   → Issue breakdown
   → Rating trends

4. When patterns emerge (≥3 occurrences):
   feedback-skill patterns
   → Shows recurring issues
   → Recommends rule update commands

5. User manually updates rules:
   writing-rules-skill style --type X --update
   writing-rules-skill structure --type X --update
   writing-rules-skill persona --audience-type X --update

No automation. User decides when to act.

---

Issue Categories

Simple, content-focused categories:

Category	Description	Related Rule
tone	Wrong tone or style	style
structure	Poor organization	structure
info	Missing information	persona, sources
comprehension	Hard to understand	style, structure
length	Too long or short	persona
examples	Code example issues	structure
other	Manual review	-

---

Integration Points

From content-writing-skill

Optional integration (not required):

# After draft creation
echo ""
echo "Rate this draft? (y/N): "
read -r RESPONSE

if [ "$RESPONSE" = "y" ] || [ "$RESPONSE" = "Y" ]; then
    feedback-skill rate "$DRAFT_PATH"
fi

To writing-rules-skill

patterns.md recommends commands:

Tone Issues (5× in last 30 days)
→ writing-rules-skill style --type technical-docs --update

Structure Issues (3× in last 30 days)
→ writing-rules-skill structure --type tutorial --update

User copies and runs command to update rules.

---

Configuration

Minimal configuration in .kurt/feedback/feedback-config.yaml:

feedback:
  enabled: true
  min_pattern_frequency: 3  # Minimum occurrences to show pattern
  default_time_window_days: 30

Removed from config:

• Issue mappings with automated commands (too complex)
• Improvement execution settings (no automation)
• Workflow-related configuration (workflows removed)

---

Design Principles

1. Simple and lightweight: Just collect → analyze → recommend
2. Pattern-based: Only show issues that occur multiple times
3. Manual execution: User runs update commands (no automation)
4. Non-blocking: Feedback collection never interrupts workflow
5. Content-focused: Only content quality (no projects/workflows)
6. Privacy-conscious: Minimal data storage

---

Example Usage

Rate a draft:

feedback-skill rate projects/my-tutorial/draft.md

View feedback trends:

feedback-skill dashboard
feedback-skill dashboard --days 7

Check for patterns:

feedback-skill patterns
feedback-skill patterns --min-frequency 5

After pattern identified, update rules:

# Copy recommended command from patterns output
writing-rules-skill style --type technical-docs --update

---

Getting Started

1. Create content (drafts, outlines)

2. Rate content occasionally:

   feedback-skill rate path/to/draft.md
   

3. After several ratings, check dashboard:

   feedback-skill dashboard
   

4. When patterns emerge, check recommendations:

   feedback-skill patterns
   

5. Update rules based on patterns:

   writing-rules-skill style --type X --update
   

---

What Changed from Previous Version

Removed:

• Project plan feedback (Loop 2)
• Workflow retrospectives (Loop 3)
• Automated improvement execution
• Validation and effectiveness tracking
• Complex feedback loop completion metrics
• Multiple feedback types (now just content quality)

Kept (simplified):

• Content rating with issue identification
• Pattern analysis across feedback
• Trend visualization in dashboard
• Manual rule update recommendations

Result: ~2,000 fewer lines of code, simpler user experience

---

This skill provides lightweight feedback collection and pattern analysis to guide manual rule improvements.