cost-tracker
Cost-tracker monitors Claude Code session expenses and token usage by tracking operation costs, setting spending limits, and recommending optimization strategies. Use this skill when checking mid-session costs, establishing budget alerts for specific tasks, or planning work to stay within spending targets across bug fixes, features, refactors, and code reviews.
git clone --depth 1 https://github.com/rohitg00/pro-workflow /tmp/cost-tracker && cp -r /tmp/cost-tracker/skills/cost-tracker ~/.claude/skills/cost-trackerSKILL.md
# Cost Tracker
Monitor and optimize Claude Code session costs.
## Trigger
Use when:
- Checking session costs
- Setting budget alerts
- Optimizing token spend
- Planning multi-session work
## Cost Awareness
### Check Current Costs
```bash
# Session cost is shown at the end of each session
# Mid-session: check the status bar or run /cost
```
### Cost Drivers
| Operation | Relative Cost | Optimization |
|-----------|--------------|-------------|
| Large file reads | High | Use offset/limit params |
| Broad grep searches | Medium | Scope to specific dirs |
| Subagent spawning | High (new context) | Reuse agents via SendMessage |
| Repeated tool calls | Cumulative | Batch operations |
| MCP tool calls | Variable | Minimize round-trips |
| Model selection | 3-10x difference | Use haiku for simple tasks |
### Token Budget by Task Type
| Task | Typical Cost | Budget Alert |
|------|-------------|-------------|
| Bug fix | $0.10-0.50 | $1.00 |
| Feature (small) | $0.50-2.00 | $3.00 |
| Feature (large) | $2.00-8.00 | $10.00 |
| Refactor | $1.00-5.00 | $7.00 |
| Code review | $0.20-1.00 | $2.00 |
### Tool-Call Budgets
Set explicit budgets by task complexity:
| Task Type | Tool-Call Budget | Wrap-Up At |
|-----------|-----------------|------------|
| Quick fix / lookup | 20 calls | 15 |
| Bug fix | 30 calls | 25 |
| Feature (small) | 50 calls | 40 |
| Feature (large) | 80 calls | 65 |
| Refactor | 50 calls | 40 |
At the wrap-up threshold: commit progress, assess remaining work, decide whether to continue or start fresh.
### Optimization Strategies
1. **Scope prompts tightly** — "Fix the auth bug in src/auth/login.ts" vs "Fix the auth bug"
2. **Use the right model** — Haiku for simple lookups, Sonnet for features, Opus for architecture
3. **Delegate to subagents** — Search/explore operations in subagents keep main context lean
4. **Compact proactively** — Don't wait for auto-compact; compact at task boundaries
5. **Read selectively** — Use `offset` and `limit` params for large files
6. **Batch operations** — Multiple independent tool calls in one message
7. **One-pass discipline** — Write complete solution, test once, stop if green
8. **No re-reads** — Don't re-read unchanged files; trust cached knowledge
9. **Read before write** — Never write a file without reading it first
10. **Kill output bloat** — No sycophantic openers, no closing fluff, no prompt restatement
## Budget Alerts
Set mental checkpoints:
- **50% budget** — Are you on track? Should you compact?
- **80% budget** — Wrap up current task, avoid new exploration
- **100% budget** — Commit what you have, start fresh session
## Output
```text
COST TRACKER
Session cost: $X.XX
Token usage: [input]K in / [output]K out
Cache hit rate: ~XX%
Top cost drivers:
1. [operation] — $X.XX
2. [operation] — $X.XX
Optimization tips:
- [specific suggestion]
```
## Rules
- Track costs as awareness, not hard limits
- Never sacrifice code quality to save tokens
- Compact at task boundaries, not mid-task
- Use subagents for exploration-heavy workCoordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
Analyzes and optimizes context window usage across sessions. Use when context feels bloated, sessions run slow, or approaching compaction limits.
Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.