Openclaw

Skill neardws/token-sisyphus/skills/openclaw

Burn LLM tokens toward a target count to satisfy corporate AI usage KPIs. Trigger when user says: burn tokens, consume tokens, fill KPI, push the boulder, sisyphus mode, or specifies a token target like "burn 100k tokens". Supports OpenAI, Claude, Gemini, and any OpenAI-compatible API.From its SKILL.md

Install

npx -y skills add neardws/token-sisyphus --skill openclaw

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SKILL.md

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token-sisyphus

Push the boulder. Watch it roll back. At least your KPI is green.

The burn script is bundled at scripts/burn.py — no external download required.

Setup

Install the SDK for your chosen provider:

pip install openai              # for openai provider (default)
pip install anthropic           # for claude provider
pip install google-generativeai # for gemini provider

Set the corresponding env var:

Provider	Env var
OpenAI / compatible	`OPENAI_API_KEY`
Claude	`ANTHROPIC_API_KEY`
Gemini	`GEMINI_API_KEY`

Usage

Run the bundled script directly:

python {skillDir}/scripts/burn.py --target <amount> [options]

  --target       Token count: 50000, 100k, 1m  (required)
  --provider     openai | claude | gemini  (default: openai)
  --model        Model name (omit to use provider default)
  --api-key      API key (falls back to env var)
  --base-url     Custom endpoint URL (openai provider only)
  --max-tokens   Max tokens per request (default: 500)
  --delay        Seconds between requests (default: 0.5)
  --dry-run      Simulate without real API calls

Common invocations

# OpenAI (default, gpt-4o-mini)
python {skillDir}/scripts/burn.py --target 100k

# Claude Haiku
python {skillDir}/scripts/burn.py --target 100k --provider claude --model claude-3-haiku-20240307

# Gemini Flash
python {skillDir}/scripts/burn.py --target 100k --provider gemini --model gemini-1.5-flash

# DeepSeek
python {skillDir}/scripts/burn.py --target 100k --base-url https://api.deepseek.com/v1 --model deepseek-chat

# Qwen / Tongyi
python {skillDir}/scripts/burn.py --target 100k --base-url https://dashscope.aliyuncs.com/compatible-mode/v1 --model qwen-turbo

# Kimi / Moonshot
python {skillDir}/scripts/burn.py --target 100k --base-url https://api.moonshot.cn/v1 --model moonshot-v1-8k

# Dry run (no real API calls, no cost)
python {skillDir}/scripts/burn.py --target 100k --dry-run

Provider defaults

Provider	Default model
openai	gpt-4o-mini
claude	claude-3-haiku-20240307
gemini	gemini-1.5-flash

Cost note

Each request uses up to --max-tokens (default 500) tokens. Running --target 100k will make ~200 requests. Use --dry-run first to verify behavior without incurring API costs. Prefer scoped/limited API keys when testing.