Skill: neardws/token-sisyphus (version 1.0.2)

--- name: token-sisyphus description: > 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. metadata: openclaw: requires: bins: [] env: - name: OPENAI_API_KEY description: "API key for OpenAI or compatible provider (DeepSeek, Qwen, Kimi, etc.)" optional: true - name: ANTHROPIC_API_KEY description: "API key for Anthropic Claude" optional: true - name: GEMINI_API_KEY description: "API key for Google Gemini" optional: true install: - id: openai-sdk kind: pip package: openai label: "Install OpenAI SDK (required for openai provider)" optional: true - id: anthropic-sdk kind: pip package: anthropic label: "Install Anthropic SDK (required for claude provider)" optional: true - id: gemini-sdk kind: pip package: google-generativeai label: "Install Gemini SDK (required for gemini provider)" optional: true --- # 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: ```bash 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 ```bash # 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.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)