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complexity-scorer-5-confidence-scoring

vamseeachanta
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À propos

Cette sous-compétence ajoute un score de confiance aux estimations de complexité, indiquant la fiabilité de l'évaluation. Elle calcule la confiance en fonction de la longueur du texte et des correspondances de mots-clés, fournissant aux développeurs une mesure de certitude pour le scoring automatisé. Utilisez-la lorsque vous avez besoin d'évaluer la fiabilité d'une classification de complexité.

Installation rapide

Claude Code

Recommandé
Principal
npx skills add vamseeachanta/workspace-hub
Commande PluginAlternatif
/plugin add https://github.com/vamseeachanta/workspace-hub
Git CloneAlternatif
git clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/complexity-scorer-5-confidence-scoring

Copiez et collez cette commande dans Claude Code pour installer cette compétence

Documentation

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"
}

Dépôt GitHub

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

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