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token-usage

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Track, aggregate, and report OpenClaw token usage and costs across sessions.

What it does

Track, aggregate, and report OpenClaw token usage and costs across sessions.

The skill document

Token Usage Tracker

Parse OpenClaw and Codex session JSONL files to extract token usage, aggregate by date/model/session, and generate cost reports across providers.

When to Use

  • User asks "how many tokens did I use today/this week"
  • User wants to know session costs or model breakdown
  • Budget monitoring and anomaly detection
  • Before/after optimization comparisons

Workflow

  1. Locate sessions — Find .jsonl files in OpenClaw agent sessions and nested Codex rollout sessions
  2. Parse usage — Extract OpenClaw message usage or Codex event_msg/token_count per-turn usage
  3. Aggregate — Group by date, model, session ID
  4. Report — Output summaries, trends, cost estimates

Commands

Parse and aggregate current sessions (OpenClaw + Codex)

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --today

Weekly report with cost estimates

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --week --costs

Report by cron job (daily breakdown per job)

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --week --by-cron

Weekly cron report with costs (JSON output)

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --week --by-cron --costs --json

All-time summary by model

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --all --by-model

Export to JSON for external dashboards

python3 ~/.openclaw/skills/token-usage/scripts/parse.py --week --json > /tmp/token-report.json

Data Format

Sessions are stored as JSONL with lines like:

{"type":"message","message":{"role":"assistant",...},"usage":{"input":1000,"output":500,"totalTokens":1500},...}

Cost Estimation

Uses model pricing from scripts/pricing.json (user-editable). The bundled table includes Kimi, OpenAI/GPT, Anthropic/Claude, and OpenRouter models. Unknown models are reported without a cost estimate rather than silently priced as Kimi.

Default examples (USD per 1M tokens):

  • Kimi k2.7: $0.50/1M input, $2.00/1M output
  • Claude Sonnet 4: $3.00/1M input, $15.00/1M output
  • GPT-4o: $2.50/1M input, $10.00/1M output

Costs are approximate. Cache read/write pricing applied when available.

Important: What "Total" Means

The script reports input + output tokens as the usage metric. This is the actual new token consumption per turn.

The totalTokens field in session files includes cacheRead (cached context window), which gets re-counted at every turn. Summing totalTokens across messages would massively overcount — a 10K context used for 100 turns would appear as 1M tokens. The script avoids this by only summing input and output.

Output Locations

  • Daily summaries: ~/.openclaw/skills/token-usage/logs/YYYY-MM-DD.md
  • Weekly reports: ~/.openclaw/skills/token-usage/logs/week-YYYY-Www.md
  • Raw JSON exports: user-specified or /tmp/token-usage-*.json

Limitations

  • OpenClaw records are parsed from message.usage; Codex rollouts are parsed from payload.info.last_token_usage in token_count events
  • input + output is the new-usage metric; Codex cached input is reported separately as cacheRead
  • Historical sessions before JSONL format are not supported
  • Costs are estimates; actual billing may differ

Related skills

OpenClaw usage and performance reporting. Parse session JSONL to answer how long each agent task took, which tools/skills/models were used, and how many tokens were consumed — zero dependency, local only, no cost dimension (token is the primary metric). Read-only: never modifies any file, aggregates statistics only, never leaks conversation content. Use when the user asks about token usage, task duration, slowest tools, skill usage, or per-agent consumption (今天花了多少 token/哪个工具最慢/ 任务耗时/用量报告), or scheduled via cron. 中文:OpenClaw 用量与性能查询。 解析 session JSONL,回答每次 agent 任务耗时、所用工具/技能/模型、token 消耗。零依赖纯本地,不提供成本维度(token 为主指标)。只读:不修改任何 文件,只输出聚合统计,不泄露会话内容。用户问 token 用量、任务耗时、 最慢工具、技能使用、按 agent 消耗时使用。cron 每日日报为可选项,用户 自行设置。

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