score

name	score
description	Score a prompt for context engineering quality. Use when the user asks to score, analyze, or optimize a prompt, or when reviewing prompt quality before sending to an LLM.

Score Prompt

Score the provided prompt text for context engineering quality using the ContextStellar scoring API.

What to do

1. Take the prompt text from $ARGUMENTS. If no arguments provided, ask the user to paste or describe the prompt they want scored.

2. Call the ContextStellar hooks endpoint to score the prompt:

curl -s -X POST "${CONTEXTSTELLAR_BASE_URL:-https://contextstellar.com}/api/v1/hooks/claude-code" \
  -H "Authorization: ${CONTEXTSTELLAR_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "{
    \"sessionId\": \"manual-score-$(date +%s)\",
    \"type\": \"PreToolUse\",
    \"toolName\": \"ManualScore\",
    \"toolInput\": { \"content\": $(echo "$PROMPT_TEXT" | jq -Rs .) }
  }"

3. Present the results clearly:

   • Overall Score and Grade (A+ through F)
   • Dimension Breakdown — show each of the 5 dimensions with their individual scores
   • Tips — list the actionable optimization suggestions
   • Token Count and potential Token Savings

4. If the score is below B (< 70), proactively suggest specific improvements the user can make.

Scoring Dimensions

Dimension	What It Measures
Token Utilization (25%)	Waste: politeness, filler, intensifiers, redundancy
Structural Clarity (23%)	XML tags, lists, headers, code blocks, imperative keywords
Specificity (20%)	Numbers, format keywords, role assignment, examples, constraints
Content Density (17%)	Lexical diversity, n-gram repetition
Cache-Friendliness (15%)	Timestamps, UUIDs, date refs, volatile data positioning

Grade Scale

• A+ (90+): Excellent — production-ready prompt
• A (80-89): Great — minor optimizations possible
• B (70-79): Good — some waste patterns detected
• C (60-69): Fair — significant optimization opportunity
• D (50-59): Poor — major restructuring recommended
• F (<50): Failing — fundamental issues