Skills

Cost

Deep cost exploration and transparency.

Install

npx skills add SethGammon/Citadel --skill cost -g -a claude-code -y
Repository
SethGammon/Citadel927
Category
AI and agents
Updated
5d ago
License
MIT
Context cost
Mediumabout 1,532 tokens
Runs scripts
No, instructions only

What it does

Deep cost exploration and transparency. Shows real token usage, session costs, campaign spend, burn rates, and model breakdown. Reads Claude Code's native session data for exact numbers. Complements /dashboard with focused cost views.

/cost -- Session & Campaign Cost Explorer

When to Use

  • /cost -- current session cost and burn rate
  • /cost today -- today's total spend
  • /cost week -- this week's spend
  • /cost campaign {slug} -- total spend for a specific campaign
  • /cost all -- lifetime cost summary
  • When /do routes "how much", "what's the cost", "spending", "tokens", "burn rate"

Inputs

Optional arguments parsed from user message:

  • today -- filter to today's sessions
  • week -- filter to last 7 days
  • campaign {slug} -- filter to a specific campaign
  • all -- show all-time data
  • No argument -- show current session

Protocol

Step 1: READ REAL DATA

Run the session-tokens.js script to get real token data:

node scripts/session-tokens.js              # current/latest session
node scripts/session-tokens.js --today      # today's sessions
node scripts/session-tokens.js --all        # all sessions (use for week/all/campaign)

Also read:

  • .planning/telemetry/cost-tracker-state.json for live burn rate
  • .planning/telemetry/session-costs.jsonl for campaign attribution
  • scripts/pricing.json to show which pricing is being used

If session-tokens.js is not available or fails, fall back to session-costs.jsonl data and clearly mark output as "(estimated)".

Step 2: RENDER BASED ON SCOPE

Current session (/cost with no args):

=== Session Cost Report ===
Session: {sessionId (first 8 chars)}
Started: {relative time} ({absolute time})
Duration: {minutes} min

Tokens:
  Input:          {N} tokens
  Output:         {N} tokens
  Cache creation: {N} tokens
  Cache read:     {N} tokens
  Total:          {N} tokens

Cost: ${total}
Burn rate: ${rate}/min
Messages: {N} ({N} main + {N} across {N} subagents)

Model breakdown:
  claude-opus-4-6:         {N} messages (${cost}, {pct}% of spend)
  claude-haiku-4-5:        {N} messages (${cost}, {pct}% of spend)
Read the whole SKILL.md on GitHub

More in AI and agents