subagent-driven-development
OBobra/superpowers298k2,631 new stars in the last 7 days
task-token-usage
Analyzes Claude Code session traces (JSONL) and draft task files to report token usage per task. Use when asked about token usage, session costs, or task efficiency metrics.
- Star
- 1,152
- Category
- Extending agents
- License
- Apache-2.0
- Last commit
- Oct 13, 2026
coworker/skills/task-token-usage/SKILL.md
View on GitHubTask Token Usage
Analyzes Claude Code conversation traces to report token consumption per task.
When to Use
- "list tasks with token usage"
- "show me token usage for each task"
- "how many tokens did task X use?"
- "what tasks ran in the last N hours?"
- "compare token usage across tasks"
How It Works
- Scans
~/.claude/projects/<project>/for JSONL session traces - Extracts
input_tokens,output_tokens,cache_read_input_tokensfrom each assistant message - Optionally matches sessions to draft task files in
coworker/tasks/issues/draft/ - Prints a summary table grouped by task
Usage
Run the bundled script:
python3 coworker/skills/task-token-usage/scripts/list-tasks.py [OPTIONS]
Options
| Flag | Description |
|---|---|
--recent N | Only show sessions from last N hours (default: 24) |
-d, --detail | Per-session breakdown instead of grouped summary |
-a, --all | Show all sessions (no time filter) |
Examples
# Summary of last 12 hours
python3 coworker/skills/task-token-usage/scripts/list-tasks.py --recent 12
# Detailed per-session view for all time
python3 coworker/skills/task-token-usage/scripts/list-tasks.py --all --detail
# Default: last 24 hours, grouped summary
python3 coworker/skills/task-token-usage/scripts/list-tasks.py
Output Columns (Summary Mode)
| Column | Description |
|---|---|
| Task | Task name (matched from draft files or first step description) |
| Runs | Number of evaluation sessions for this task |
| In Tok | Total input tokens across all runs |
| Out Tok | Total output tokens across all runs |
| Cache | Total cache-read + cache-creation tokens |
| TOTAL | Sum of all tokens |
| Avg/run | Average total tokens per run |
Output Columns (Detail Mode)
| Column | Description |
|---|---|
| Time | When the session ended |
| Task | Matched task name |
| In | Input tokens |
| Out | Output tokens |
| CacheR | Cache-read tokens |
| TOTAL | Total tokens |
| Model | AI model used |
Token Pricing (Approximate)
The script does not compute cost, but you can estimate:
| Model | Input (per 1M) | Output (per 1M) | Cached (per 1M) |
|---|---|---|---|
| claude-sonnet-4.6 | $3.00 | $15.00 | $0.30 |
| claude-opus-4 | $15.00 | $75.00 | $1.50 |
| claude-haiku-4.5 | $1.00 | $5.00 | $0.10 |
Cache tokens account for ~96% of total usage in typical evaluation sessions.
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