Real-time observability for OpenClaw agents — token usage, API cost, context health, and smart alerts. Zero config. 100% local.
Universal LLM token counting and cost management. Track spending, set budgets, compare providers.
An open-source, local-first framework for building multi-model, multi-agent RAG pipelines.
Claude Code Skill — estimate and compare LLM API costs across OpenAI, Anthropic, Google, DeepSeek, Mistral. Per-token pricing, batch/caching discounts, workload templates, cross-provider comparison.
Benchmark latency and route fit for OpenAI-compatible AI API endpoints.
Local, single-file HTML dashboard for Claude Code usage and estimated USD cost — token totals across all classes (input/output/cache), per-model spend at list API prices, live current-day data, MCP activity, web research, AI-clustered themes. One uv-runnable Python script.
Passive cost memory for AI Assisted Coding— detects paid services, tracks spend, injects budget context into your AI coding sessions.
Calculate token counts for text using various LLM tokenizers to estimate API costs and context limits
Track AI API costs per task, model, and project. Stop guessing your spend.
LLM Cost Optimizer that routes requests to cheaper models, caches semantically similar queries, and compresses prompts to reduce AI API spending by up to 70%. Python backend + Next.js dashboard.
AI API cost monitoring tool - Track and manage costs across multiple AI providers
🛡️ Cost circuit breaker for Claude Code — hard budget limits, auto-kill runaway sessions, anomaly detection. Zero dependencies.
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