How do I install the LLM Cost Tracker skill?

Run npx skillmds@latest add lord1egypt/llm-cost-tracker in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is LLM Cost Tracker safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with LLM Cost Tracker?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is LLM Cost Tracker free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published LLM Cost Tracker?

Lord1Egypt (@lord1egypt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

LLM Cost Tracker by lord1egypt — Agent Skill

Name: LLM Cost Tracker
Rating: 4.666666666666667 (3 reviews)
Author: Lord1Egypt

LLM Cost Tracker

Track OpenClaw LLM token usage and cost from OpenRouter API. Reports: last 24h, 7d, 30d, 90d, 365d with model breakdown. Skills that trigger this: - "llm cost", "token usage", "openrouter cost", "llm spend", "daily cost report" → runs run_tracker.py - "collect usage data" → runs collect_usage.py (populates DB silently) When "collect usage data" is received (e.g. from a cron job), run: python3 scripts/collect_usage.py and return "Done" — do NOT send any message to Telegram or any chat.

Lord1Egypt Updated Sep 8, 2026 2 repo stars

File contents

llm-cost-tracker

Track and report LLM token usage and cost for OpenClaw via OpenRouter.

Quick Start

python3 scripts/collect_usage.py --init      # first-time: create DB + backfill
python3 scripts/run_tracker.py               # telegram report (default)
python3 scripts/run_tracker.py --output terminal  # full terminal report
python3 scripts/run_tracker.py --output debug     # per-request debug

Core Design

Source of truth: usage.cost.total from OpenRouter — never recomputed from token counts
Data source: OpenClaw session JSONL files (including .reset files from context compaction)
Deduplication: by openrouter_request_id — safe to re-run backfill anytime
Time windows: 24h rolling (UTC); 7d/30d/90d/365d calendar days (configurable timezone)

Schema: `request_facts`

Column	Source
openrouter_request_id	responseId (unique key)
created_at_utc	entry timestamp
model	model ID
prompt_tokens	usage.input
completion_tokens	usage.output
cached_tokens	usage.cacheRead
cache_write_tokens	usage.cacheWrite
reasoning_tokens	usage.reasoning
total_tokens	usage.totalTokens
billed_cost	usage.cost.total (canonical)

Configuration

config/env.json (all fields optional):

{
  "SESSIONS_DIR": "",
  "TIMEZONE": "Asia/Hong_Kong",
  "UTC_OFFSET_HOURS": 8
}

SESSIONS_DIR: override session file location (empty = auto-detect)
TIMEZONE / UTC_OFFSET_HOURS: for calendar-day window calculations
API key: auto-detected from ~/.openclaw/agents/main/agent/auth-profiles.json or OPENROUTER_API_KEY env var

Scheduled Reports

openclaw cron add --name "llm-cost:collect" --message "collect usage data" \
  --cron "5 0 * * *" --tz "Asia/Hong_Kong" --session isolated --no-deliver

openclaw cron add --name "llm-cost:daily" --message "llm cost" \
  --cron "0 9 * * *" --tz "Asia/Hong_Kong" --session isolated

---name: llm-cost-trackerdescription: Track OpenClaw LLM token usage and cost from OpenRouter API. Reports: last 24h, 7d, 30d, 90d, 365d with model breakdown. Skills that trigger this: - "llm cost", "token usage", "openrouter cost", "llm spend", "daily cost report" → runs run_tracker.py - "collect usage data" → runs collect_usage.py (populates DB silently) When "collect usage data" is received (e.g. from a cron job), run: python3 scripts/collect_usage.py and return "Done" — do NOT send any message to Telegram or any chat.---# llm-cost-trackerTrack and report LLM token usage and cost for OpenClaw via OpenRouter.## Quick Start```bashpython3 scripts/collect_usage.py --init # first-time: create DB + backfillpython3 scripts/run_tracker.py # telegram report (default)python3 scripts/run_tracker.py --output terminal # full terminal reportpython3 scripts/run_tracker.py --output debug # per-request debug```## Core Design- **Source of truth:** `usage.cost.total` from OpenRouter — never recomputed from token counts- **Data source:** OpenClaw session JSONL files (including `.reset` files from context compaction)- **Deduplication:** by `openrouter_request_id` — safe to re-run backfill anytime- **Time windows:** 24h rolling (UTC); 7d/30d/90d/365d calendar days (configurable timezone)## Schema: `request_facts`| Column | Source ||--------|--------|| openrouter_request_id | responseId (unique key) || created_at_utc | entry timestamp || model | model ID || prompt_tokens | usage.input || completion_tokens | usage.output || cached_tokens | usage.cacheRead || cache_write_tokens | usage.cacheWrite || reasoning_tokens | usage.reasoning || total_tokens | usage.totalTokens || billed_cost | usage.cost.total (canonical) |## Configuration`config/env.json` (all fields optional):```json{ "SESSIONS_DIR": "", "TIMEZONE": "Asia/Hong_Kong", "UTC_OFFSET_HOURS": 8}```- `SESSIONS_DIR`: override session file location (empty = auto-detect)- `TIMEZONE` / `UTC_OFFSET_HOURS`: for calendar-day window calculations- API key: auto-detected from `~/.openclaw/agents/main/agent/auth-profiles.json` or `OPENROUTER_API_KEY` env var## Scheduled Reports```bashopenclaw cron add --name "llm-cost:collect" --message "collect usage data" \ --cron "5 0 * * *" --tz "Asia/Hong_Kong" --session isolated --no-deliveropenclaw cron add --name "llm-cost:daily" --message "llm cost" \ --cron "0 9 * * *" --tz "Asia/Hong_Kong" --session isolated```

Frequently asked questions