MCP HubMCP Hub
Zurück zu Fähigkeiten

complexity-scorer-1-keyword-based-scoring

vamseeachanta
Aktualisiert Today
7 Ansichten
3
2
3
Auf GitHub ansehen
Andereword

Über

Diese Fähigkeit addiert +1 zur Aufgabenkomplexitätsbewertung, wenn mittelschwere Schlüsselwörter wie "implementieren", "Funktion" oder "Test" in einer Anfrage erkannt werden. Sie ist Teil eines modularen Bewertungssystems, in dem andere Teilfähigkeiten hoch- oder niedrigkomplexe Begriffe verarbeiten. Nutzen Sie sie, um automatisch die Schwierigkeitseinschätzung von Aufgaben basierend auf einer Schlüsselwortanalyse in Entwicklungs-Workflows anzupassen.

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-1-keyword-based-scoring

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

Dokumentation

1. Keyword-Based Scoring (+1)

1. Keyword-Based Scoring

Define keyword categories with weights:

#!/bin/bash
# ABOUTME: Keyword-based complexity scoring
# ABOUTME: Pattern from workspace-hub suggest_model.sh

# Keyword categories with associated complexity impact
# High complexity keywords (score +3)
HIGH_COMPLEXITY="architecture|refactor|design|security|complex|multi-file|algorithm|optimization|strategy|planning|cross-repository|performance|migration|integration"

# Medium complexity keywords (score +1)
MEDIUM_COMPLEXITY="implement|feature|bug|fix|code review|documentation|test|update|add|create|build|configure|setup"

# Low complexity keywords (score -2)
LOW_COMPLEXITY="check|status|simple|quick|template|list|grep|find|search|summary|validation|exists|show|display|count|verify"

# Score based on keywords
score_keywords() {
    local text="$1"
    local text_lower=$(echo "$text" | tr '[:upper:]' '[:lower:]')
    local score=0

    # Check high complexity first (mutually exclusive)
    if echo "$text_lower" | grep -qE "$HIGH_COMPLEXITY"; then
        ((score+=3))
    elif echo "$text_lower" | grep -qE "$MEDIUM_COMPLEXITY"; then
        ((score+=1))
    elif echo "$text_lower" | grep -qE "$LOW_COMPLEXITY"; then
        ((score-=2))
    fi

    echo $score
}

# Usage
task="Design the authentication system architecture"
score=$(score_keywords "$task")
echo "Complexity score: $score"  # Output: 3

2. Multi-Factor Scoring

Combine multiple factors for better accuracy:

#!/bin/bash
# ABOUTME: Multi-factor complexity scoring
# ABOUTME: Combines keywords, length, context

# Factor weights
declare -A WEIGHTS=(
    ["keywords"]=3
    ["length"]=1
    ["urgency"]=1
    ["scope"]=2
)

# Score task length
score_length() {
    local text="$1"
    local word_count=$(echo "$text" | wc -w)

    if [[ $word_count -gt 20 ]]; then
        echo 2  # Long = more complex
    elif [[ $word_count -gt 10 ]]; then
        echo 1
    elif [[ $word_count -lt 5 ]]; then
        echo -1  # Short = simpler
    else
        echo 0
    fi
}

# Score urgency indicators
score_urgency() {
    local text="$1"
    local text_lower=$(echo "$text" | tr '[:upper:]' '[:lower:]')

    if echo "$text_lower" | grep -qE "urgent|asap|critical|emergency|immediately"; then
        echo 2
    elif echo "$text_lower" | grep -qE "soon|priority|important"; then
        echo 1
    else
        echo 0
    fi
}

# Score scope indicators
score_scope() {
    local text="$1"
    local text_lower=$(echo "$text" | tr '[:upper:]' '[:lower:]')

    if echo "$text_lower" | grep -qE "all|every|entire|complete|full|comprehensive"; then
        echo 2
    elif echo "$text_lower" | grep -qE "multiple|several|various|many"; then
        echo 1
    elif echo "$text_lower" | grep -qE "single|one|specific|particular"; then
        echo -1
    else
        echo 0
    fi
}

# Combined scoring
calculate_complexity() {
    local text="$1"
    local total=0

    local keyword_score=$(score_keywords "$text")
    local length_score=$(score_length "$text")
    local urgency_score=$(score_urgency "$text")
    local scope_score=$(score_scope "$text")

    total=$((keyword_score * ${WEIGHTS[keywords]} +
             length_score * ${WEIGHTS[length]} +
             urgency_score * ${WEIGHTS[urgency]} +
             scope_score * ${WEIGHTS[scope]}))

    echo $total
}

GitHub Repository

vamseeachanta/workspace-hub
Pfad: .claude/skills/_core/bash/complexity-scorer/1-keyword-based-scoring

Verwandte Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

Skill ansehen

cloudflare-turnstile

Meta

This skill provides comprehensive guidance for implementing Cloudflare Turnstile as a CAPTCHA-alternative bot protection system. It covers integration for forms, login pages, API endpoints, and frameworks like React/Next.js/Hono, while handling invisible challenges that maintain user experience. Use it when migrating from reCAPTCHA, debugging error codes, or implementing token validation and E2E tests.

Skill ansehen

cloudflare-cron-triggers

Testen

This skill provides comprehensive knowledge for implementing Cloudflare Cron Triggers to schedule Workers using cron expressions. It covers setting up periodic tasks, maintenance jobs, and automated workflows while handling common issues like invalid cron expressions and timezone problems. Developers can use it for configuring scheduled handlers, testing cron triggers, and integrating with Workflows and Green Compute.

Skill ansehen

llamaindex

Meta

LlamaIndex is a data framework for building RAG-powered LLM applications, specializing in document ingestion, indexing, and querying. It provides key features like vector indices, query engines, and agents, and supports over 300 data connectors. Use it for document Q&A, chatbots, and knowledge retrieval when building data-centric applications.

Skill ansehen