Local, cache-aware LLM usage and cost telemetry for OpenClaw.
Local prompt-cache economics for LLM agents: split cache reads/writes from input spend, reconcile dollars to invoices, and surface concrete TTL/marker fixes.
Enterprise-grade Cost Intelligence Platform & LLM Gateway. Centralize API credentials, issue scoped child keys, enforce real-time budget limits, predict monthly spending, and proxy chat completions securely.
Git-native granular cost accounting for AI-developed repos, what did this commit cost? Reads Claude Code / Codex / Gemini CLI / aider logs, joins them to git history, and prices every commit, PR and release. Measured from real tokens, never estimated.
a local-first, multi-provider tool that captures LLM API spend and exposes it to coding agents via the Model Context Protocol
Spring Boot starter that enforces LLM cost budgets, fallback decisions, and abuse protection via a single @LLMGuarded annotation
Claude Code plugin to track token usage and costs across sessions
Your Claude Code token quantification & optimization command center. Know exactly where every token goes, why it's spent, and how to spend less — all in a native desktop app, all data stays local.
Self-hosted web dashboard for monitoring local OpenAI Codex usage, sessions, credits, cache efficiency, and account limits.
LLM cost calculator, token counter, latency benchmark, CI guardrail, MCP server, and VS Code/Cursor extension.
Track OpenClaw LLM calls, show real costs, and cut agent spend with a local dashboard and no data leaving your machine
Open FinOps and governance data plane for FOCUS 1.2 cost normalization across cloud, on-prem, GPU, and AI/LLM workloads.
Shrinks what agents read: 60.6% fewer model-visible tokens, full evidence kept lossless, savings self-measured.
Experimental CLI for estimating AI-agent request costs and tracking budget assumptions across OpenAI, Anthropic and GitHub Copilot.
Read-only OpenAI API observed-spend budget gate for CI
Four-line omp statusline widget: zai coding-plan quota (provider-gated), prayer times, hijri clock, API-spend ledger (subagent-inclusive)
Token-Light, Code-Intensive (TLCI) — A design philosophy for AI agent automation. Use AI only where it's needed. 80-97% cost reduction.
Reduce AI token costs by up to 70%. One-click optimizer for Claude Code, Cursor, Codex CLI, and Gemini.
Budget enforcement and spend tracking for autonomous agents — per-agent limits, threshold alerts, cost analysis. MCP server.
GitHub profile README for Faraazuddin Mohammed's token economics open-source work
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