Overview
- Skill Key
- gerhardvr26/oken-usage-tracker
- Author
- gerhardvr26
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/gerhardvr26/oken-usage-tracker
- Latest Commit SHA
- d707e6af568e1a84854bd1f996e60b127e220166
Token usage logging, alerting, and context-compression utilities for OpenClaw. Use when you want to track per-call token usage, normalize timestamps, and reduce context sent to LLMs via summarization/compression.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 token-usage-tracker 技能。 若已安装,则直接安装 token-usage-tracker 技能。
# token-usage-tracker Quick start 1. Configure defaults in `skill-config.json` (timezone, log_folder). 2. Install scripts (examples provided) into your workspace and wire the interceptor into your message pipeline. 3. Use `scripts/context_summarizer.py` before sending large contexts to reduce token usage. What this skill provides - Logging: `token_tracker.py` writes per-call token usage to a JSONL log. Includes timestamp normalization. - Interceptor: `token_interceptor.py` example that normalizes timestamps and forwards sanitized messages to the tracker. - Alerts: `token_alerts.py` example for threshold-based alerts (no external posting by default). - Compression: `context_summarizer.py` produces short summaries to reduce token payloads. - Utilities: migration and cleanup scripts (convert timestamps, dedupe log entries). When to use - Use this skill when you want transparent per-call token accounting, to keep token usage low, or to protect sensitive/verbose contexts by summarizing before sending to the model. Files - scripts/ - token_interceptor.py — example interceptor (normalizes timestamps) - token_tracker.py — logging helper - token_alerts.py — alert examples - context_summarizer.py — compression helper - migrate_timestamps.py — migration utility - dedupe_log.py — dedupe utility - references/ - examples/systemd/ — example unit files (install manually) - skill-config.json — configurable defaults - README.md — usage and install notes Configuration See `skill-config.json` for defaults. The skill exposes: - timezone: default UTC - log_folder: default ./skills/logs (relative to OpenClaw workspace) - compression settings: summary_target_tokens, max_context_tokens Security and installation - The scripts are examples and safe by default. They do not change system state or install services automatically. - Example systemd/unit files are provided in `references/systemd/` — apply them manually after review. License: MIT (adapt as you prefer)
token-usage-tracker Overview This skill provides a set of example scripts to track per-call token usage, normalize timestamps, and compress large contexts before sending them to an LLM. Installation (manual) 1. Review scripts in `scripts/` and adjust paths/config as needed. 2. Copy desired scripts into your active workspace or reference them from the skill folder. 3. Optionally set up systemd units found in `references/systemd/` (examples only). Defaults - Timezone: UTC - Log folder: ./skills/logs (relative to OpenClaw workspace) Notes - The scripts are intentionally minimal and well-commented. They are safe to read and run but will not modify system services automatically. - If you want, I can package this into a .skill file and run local tests. Say "package" to proceed.
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