Context Efficiency Report

SkillProductivity

Lets your agent analyze Claude Code session data and report how efficiently context and tools are used.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Context Efficiency Report skill

About this capability

Analyzes the current project's Claude Code session data and produces a context efficiency report (model usage, tool efficiency, delegation ratio, TodoWrite usage rate). Use together with context-management.md.

What this skill tells your AI

The instructions your AI receives, as published by zeuikli/claude-code-workspace in .claude/skills/context-report/SKILL.md and read by ahel’s review.

觸發條件

  • 評估一個 project 的 Claude Code 使用效率
  • 做成本最佳化分析(過高 Opus 比例時)
  • 專案完成後的 session 回顧
  • 配合 .claude/rules/context-management.md 做 context 壓縮決策

執行腳本

執行以下 bash 腳本(適配 Claude Code 官方 ~/.claude/projects/ 路徑):

#!/bin/bash
CWD="${ARGUMENTS:-$(pwd)}"
PROJECT_KEY=$(echo "$CWD" | sed 's|/|-|g; s|^-||')
PROJECTS_BASE="$HOME/.claude/projects"
PROJECT_DIR="$PROJECTS_BASE/$PROJECT_KEY"

if [ ! -d "$PROJECT_DIR" ]; then
  echo "No session data found for: $CWD"
  echo "Looking in: $PROJECT_DIR"
  echo "Available projects:"
  ls "$PROJECTS_BASE" 2>/dev/null | head -10
  exit 1
fi

echo "╔══════════════════════════════════════════════════════════════════╗"
printf "║  Context Efficiency Report: %-35s║\n" "$(basename "$CWD" | head -c 34)"
echo "╚══════════════════════════════════════════════════════════════════╝"
echo "Project: $CWD"
echo ""

# Session counts
session_count=$(find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" ! -name "agent-*.jsonl" 2>/dev/null | wc -l | tr -d ' ')
agent_count=$(find "$PROJECT_DIR" -maxdepth 1 -name "agent-*.jsonl" 2>/dev/null | wc -l | tr -d ' ')
echo "📁 SESSIONS"
echo "────────────────────────────────────────────────────────────────────"
echo "Main Sessions:  $session_count"
echo "Agent Sessions: $agent_count"
if [ "$session_count" -gt 0 ]; then
  ratio=$(echo "scale=2; $agent_count / $session_count" | bc)
  echo "Delegation Ratio: ${ratio}:1"
fi
echo ""

# Model usage
echo "🤖 MODEL USAGE"
echo "────────────────────────────────────────────────────────────────────"
find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" -size +1k -exec cat {} + 2>/dev/null | \
  jq -r 'select(.message.model != null) | .message.model' 2>/dev/null | \
  sort | uniq -c | sort -rn
echo ""

# Tool usage top 15
echo "🔧 TOOL USAGE (top 15)"
echo "────────────────────────────────────────────────────────────────────"
find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" -size +1k -exec cat {} + 2>/dev/null | \
  jq -r '.message.content[]? | select(.type == "tool_use") | .name' 2>/dev/null | \
  sort | uniq -c | sort -rn | head -15
echo ""

# Data size
echo "📊 DATA SIZE"
echo "────────────────────────────────────────────────────────────────────"
total_size=$(du -sh "$PROJECT_DIR" 2>/dev/null | cut -f1)
msg_count=$(find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" -exec cat {} + 2>/dev/null | wc -l | tr -d ' ')
echo "Total Size:      $total_size"
echo "Message Records: $msg_count"
echo ""

# Collect data once
all_tools=$(find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" -size +1k -exec cat {} + 2>/dev/null | \
  jq -r '.message.content[]? | select(.type == "tool_use") | .name' 2>/dev/null)
all_models=$(find "$PROJECT_DIR" -maxdepth 1 -name "*.jsonl" -size +1k -exec cat {} + 2>/dev/null | \
  jq -r '.message.model // empty' 2>/dev/null)

# Model counts
opus=$(echo "$all_models" | grep -c "opus" || echo 0)
sonnet=$(echo "$all_models" | grep -c "sonnet" || echo 0)
haiku=$(echo "$all_models" | grep -c "haiku" || echo 0)
model_total=$((opus + sonnet + haiku))

# Tool counts
bash_count=$(echo "$all_tools" | grep -c "^Bash$" || echo 0)
grep_count=$(echo "$all_tools" | grep -c "^Grep$" || echo 0)
glob_count=$(echo "$all_tools" | grep -c "^Glob$" || echo 0)
todo_count=$(echo "$all_tools" | grep -c "^TodoWrite$" || echo 0)

# Scoring (100 pts)
score=0
warnings=""

# 1. Model efficiency (30 pts):Opus ≤50% = 30pts,100% Opus = 0pts
if [ "$model_total" -gt 0 ]; then
  opus_pct=$((opus * 100 / model_total))
  model_score=$((30 - (opus_pct > 50 ? (opus_pct - 50) * 30 / 50 : 0)))
  [ "$model_score" -lt 0 ] && model_score=0
  score=$((score + model_score))
  [ "$opus_pct" -gt 80 ] && warnings="${warnings}⚠️  Opus ${opus_pct}% — 探索型任務改用 Haiku\n"
else
  opus_pct=0; model_score=15; score=$((score + 15))
fi

# 2. Delegation ratio (25 pts):3:1 = 25pts
if [ "$session_count" -gt 0 ]; then
  delegation_ratio_x100=$((agent_count * 100 / session_count))
  delegation_score=$((delegation_ratio_x100 * 25 / 300))
  [ "$delegation_score" -gt 25 ] && delegation_score=25
  score=$((score + delegation_score))
  [ "$delegation_ratio_x100" -lt 100 ] && warnings="${warnings}⚠️  委派比例低 — 多用 subagent 隔離大型任務\n"
else
  delegation_score=0
fi

# 3. Tool efficiency (25 pts):native Grep/Glob > Bash
native_search=$((grep_count + glob_count))
if [ "$bash_count" -gt 0 ]; then
  tool_ratio_x100=$((native_search * 100 / bash_count))
  tool_score=$((tool_ratio_x100 * 25 / 50))
  [ "$tool_score" -gt 25 ] && tool_score=25
  score=$((score + tool_score))
  [ "$tool_ratio_x100" -lt 10 ] && warnings="${warnings}⚠️  優先用 Grep/Glob 工具而非 bash grep/find\n"
else
  tool_score=25; score=$((score + 25))
fi

# 4. TodoWrite tracking (20 pts)
if [ "$msg_count" -gt 0 ]; then
  todo_ratio_x1000=$((todo_count * 1000 / msg_count))
  todo_score=$((todo_ratio_x1000 * 20 / 50))
  [ "$todo_score" -gt 20 ] && todo_score=20
  score=$((score + todo_score))
  [ "$todo_count" -eq 0 ] && warnings="${warnings}⚠️  未使用 TodoWrite — 複雜任務應追蹤進度\n"
else
  todo_score=0
fi

# Output score
echo "📈 EFFICIENCY SCORE"
echo "────────────────────────────────────────────────────────────────────"
echo ""
echo "  ┌─────────────────────────────────────┐"
printf "  │         SCORE: %3d / 100            │\n" "$score"
echo "  └─────────────────────────────────────┘"
echo ""
echo "  Breakdown:"
printf "    Model efficiency:    %2d/30  (Opus %d%%)\n" "$model_score" "$opus_pct"
del_ratio=$(echo "scale=1; ($agent_count + 0.0) / ($session_count + 0.001)" | bc)
printf "    Task delegation:     %2d/25  (ratio %s:1)\n" "$delegation_score" "$del_ratio"
printf "    Tool efficiency:     %2d/25  (Grep+Glob: %d, Bash: %d)\n" "$tool_score" "$native_search" "$bash_count"
printf "    Task tracking:       %2d/20  (TodoWrite: %d)\n" "$todo_score" "$todo_count"
echo ""

if [ -n "$warnings" ]; then
  echo "  Warnings:"
  printf "  $warnings"
fi

echo ""
echo "═══════════════════════════════════════════════════════════════════"
echo "Generated: $(date '+%Y-%m-%d %H:%M')"

評分標準說明

維度滿分目標說明
模型效率30Opus ≤50%搜尋/探索用 Haiku,實作用 Sonnet
委派比例25≥3:1agent session / main session
工具效率25Grep+Glob:Bash ≥50%優先用 native tools
任務追蹤20TodoWrite 有使用複雜任務應有追蹤

搭配使用

  • .claude/rules/context-management.md 對照:score <60 時觸發 Compressed 層級
  • 委派比例 <1:1 時,參考 .claude/rules/subagent-strategy.md 調整

Signals

GitHub stars
156
Forks
38
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
context-report-zeuikli
Source
github.com/zeuikli/claude-code-workspace