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complexity-scorer-5-confidence-scoring

vamseeachanta
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Anderegeneral

Über

Diese Teilfähigkeit fügt Komplexitätsschätzungen einen Konfidenzwert hinzu, der die Zuverlässigkeit der Bewertung anzeigt. Sie berechnet die Konfidenz basierend auf Textlänge und Keyword-Übereinstimmungen und bietet Entwicklern ein Maß für die Gewissheit automatisierter Bewertungen. Nutzen Sie sie, wenn Sie einschätzen müssen, wie vertrauenswürdig eine Komplexitätsklassifizierung ist.

Schnellinstallation

Claude Code

Empfohlen
Primär
npx skills add vamseeachanta/workspace-hub
Plugin-BefehlAlternativ
/plugin add https://github.com/vamseeachanta/workspace-hub
Git CloneAlternativ
git clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/complexity-scorer-5-confidence-scoring

Kopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren

Dokumentation

5. Confidence Scoring (+1)

5. Confidence Scoring

Add confidence to scoring:

#!/bin/bash
# ABOUTME: Confidence scoring for complexity estimates
# ABOUTME: Indicates reliability of the score

# Calculate confidence
calculate_confidence() {
    local text="$1"
    local confidence=50  # Base confidence

    local word_count=$(echo "$text" | wc -w)
    local keyword_matches=0
    local text_lower=$(echo "$text" | tr '[:upper:]' '[:lower:]')

    # More words = higher confidence (more context)
    if [[ $word_count -gt 15 ]]; then
        ((confidence+=20))
    elif [[ $word_count -gt 8 ]]; then
        ((confidence+=10))
    elif [[ $word_count -lt 3 ]]; then
        ((confidence-=20))
    fi

    # Keyword matches boost confidence
    for pattern in "$HIGH_COMPLEXITY" "$MEDIUM_COMPLEXITY" "$LOW_COMPLEXITY"; do
        if echo "$text_lower" | grep -qE "$pattern"; then
            ((keyword_matches++))
        fi
    done

    ((confidence += keyword_matches * 10))

    # Cap confidence
    [[ $confidence -gt 100 ]] && confidence=100
    [[ $confidence -lt 10 ]] && confidence=10

    echo $confidence
}

# Get confidence label
confidence_label() {
    local confidence="$1"

    if [[ $confidence -ge 80 ]]; then
        echo "High"
    elif [[ $confidence -ge 60 ]]; then
        echo "Medium"
    elif [[ $confidence -ge 40 ]]; then
        echo "Low"
    else
        echo "Very Low"
    fi
}

6. Historical Learning

Adjust based on past accuracy:

#!/bin/bash
# ABOUTME: Historical learning for complexity scoring
# ABOUTME: Track and adjust based on actual outcomes

HISTORY_FILE="${HOME}/.complexity-scorer/history.log"

# Log prediction vs actual
log_outcome() {
    local task="$1"
    local predicted_score="$2"
    local actual_complexity="$3"  # user-provided feedback
    local timestamp=$(date '+%Y-%m-%d_%H:%M:%S')

    mkdir -p "$(dirname "$HISTORY_FILE")"
    echo "${timestamp}|${predicted_score}|${actual_complexity}|${task}" >> "$HISTORY_FILE"
}

# Calculate prediction accuracy
calculate_accuracy() {
    local correct=0
    local total=0

    while IFS='|' read -r ts predicted actual task; do
        [[ "$ts" =~ ^#.*$ ]] && continue
        [[ -z "$ts" ]] && continue

        ((total++))

        local predicted_class=$(classify_complexity "$predicted")
        if [[ "$predicted_class" == "$actual" ]]; then
            ((correct++))
        fi
    done < "$HISTORY_FILE"

    if [[ $total -gt 0 ]]; then
        echo $((correct * 100 / total))
    else
        echo 0
    fi
}

# Find common misclassifications
find_patterns() {
    echo "Analyzing misclassification patterns..."

    while IFS='|' read -r ts predicted actual task; do
        local predicted_class=$(classify_complexity "$predicted")
        if [[ "$predicted_class" != "$actual" ]]; then
            echo "Predicted: $predicted_class, Actual: $actual"
            echo "Task: $task"
            echo "---"
        fi
    done < "$HISTORY_FILE"
}

GitHub Repository

vamseeachanta/workspace-hub
Pfad: .claude/skills/_core/bash/complexity-scorer/5-confidence-scoring

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