Agent Skill
2/7/2026token-stats
Show token economics comparing usage with turbo-search vs without. Demonstrates actual savings from search-first approach.
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mahmoudimus
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npx skills add mahmoudimus/simba
SKILL.md
| Name | token-stats |
| Description | Show token economics comparing usage with turbo-search vs without. Demonstrates actual savings from search-first approach. |
name: token-stats description: Show token economics comparing usage with turbo-search vs without. Demonstrates actual savings from search-first approach.
/token-stats - Token Economics Dashboard
Show the token savings achieved by using search-first exploration vs blind file reading.
Instructions
When the user invokes /token-stats, analyze token usage and display savings.
1. Gather Activity Data
REPO_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")
ACTIVITY_FILE="$REPO_ROOT/.simba/search/activity.log"
# Count files read this session
if [ -f "$ACTIVITY_FILE" ]; then
echo "=== Session Activity ==="
FILES_READ=$(grep -c "READ:" "$ACTIVITY_FILE" 2>/dev/null || echo "0")
FILES_EDITED=$(grep -c "EDIT:" "$ACTIVITY_FILE" 2>/dev/null || echo "0")
SEARCHES=$(grep -c "SEARCH:" "$ACTIVITY_FILE" 2>/dev/null || echo "0")
echo "Files read: $FILES_READ"
echo "Files edited: $FILES_EDITED"
echo "Searches performed: $SEARCHES"
else
echo "No activity log found for this session"
fi
2. Calculate Codebase Stats
REPO_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")
# Total files in codebase
TOTAL_FILES=$(rg --files "$REPO_ROOT" 2>/dev/null | wc -l | tr -d ' ')
# Estimate total tokens (rough: ~1.33 tokens per word, ~3 words per line)
TOTAL_LINES=$(rg -c '' "$REPO_ROOT" 2>/dev/null | awk -F: '{s+=$2} END {print s}')
ESTIMATED_TOTAL_TOKENS=$((TOTAL_LINES * 4 / 3))
echo ""
echo "=== Codebase Size ==="
echo "Total indexable files: $TOTAL_FILES"
echo "Total lines: $TOTAL_LINES"
echo "Estimated tokens: $ESTIMATED_TOTAL_TOKENS"
3. Query Memory for Historical Data
uv run python -m simba.search stats
4. Calculate and Display Economics
Based on the gathered data, calculate and present:
Token Economics Model:
| Scenario | Calculation | Typical Cost |
|---|---|---|
| Blind exploration | Read 20+ files to find relevant code | ~50,000 tokens |
| With turbo-search | Search (50 tokens) + Read 3-5 targeted files | ~5,000 tokens |
| Savings | ~90% |
Present this table to the user:
TOKEN ECONOMICS DASHBOARD
Codebase: [PROJECT_NAME]
Total Files: [X] | Total Lines: [Y] | Est. Tokens: [Z]
THIS SESSION
Searches performed: [N] (~50 tokens each)
Files read (targeted): [M] (~1,000 tokens each)
Files edited: [K]
ESTIMATED USAGE WITH PLUGIN: ~[X] tokens
ESTIMATED WITHOUT (blind read): ~[Y] tokens
SAVINGS: ~[Z]% ([Y-X] tokens saved)
HISTORICAL (ALL SESSIONS)
Total sessions: [N]
Total files tracked: [M]
Knowledge entries: [K]
Facts stored: [F]
Cumulative savings: ~[X] tokens
(Based on [S] search-first explorations)
5. Token Calculation Logic
Use these estimates for calculations:
SEARCH_COST = 50 # tokens per qmd search
FILE_READ_COST = 1000 # avg tokens per file read
BLIND_EXPLORATION_FILES = 20 # files typically read without search
TARGETED_READ_FILES = 3 # files read with search-first approach
# With plugin
with_plugin = (SEARCHES * SEARCH_COST) + (FILES_READ * FILE_READ_COST)
# Without plugin (estimate)
without_plugin = BLIND_EXPLORATION_FILES * FILE_READ_COST
# Savings
savings_tokens = without_plugin - with_plugin
savings_percent = (savings_tokens / without_plugin) * 100
6. Pro Tips
End with actionable suggestions:
Pro Tips to Maximize Savings:
- Use 'qmd search' before reading any file
- Run /remember at session end to build context
- Check /memory-stats for accumulated knowledge
- The more you use it, the smarter it gets!
Notes
- Estimates are based on typical Claude token encoding
- Actual savings vary based on codebase structure and task type
- Historical data requires using /remember consistently
Skills Info
Original Name:token-statsAuthor:mahmoudimus
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