Developer Control Plane for your AI Agents

A free, open-source book that explains how crypto actually works. 15 chapters covering Bitcoin, Ethereum, Solana, DeFi, MEV, market structure, custody, stablecoins, governance, quantum resistance, and prediction markets.

AI context optimization platform for files, conversations, RAG, code, logs and AI agents with context compression, evidence preservation, content-addressed recovery and auditable Context Receipts.

A curated list of tools, benchmarks, papers, and copy-paste configs for AI token costs: what tokens cost, where they get wasted, and how to cut the bill.

Elata Protocol is the smart contract suite for Elata's app ecosystem

Get insights into token usage for Claude code and Codex sessions with a dashboard and menu bar widget for mac

CLI and AI agent skills for the Tokenomist crypto data API: token unlocks, vesting, emissions, allocations, fundraising, burns and buybacks.

AI-Powered Crypto Analysis Dashboard!

Toolkit based on cadCAD for performing automated routine tests and future predictions for a GEB deployment

A deep technical article exploring how AI, feature engineering, and static smart-contract analysis uncover rugpull risks before humans detect them. Covers Solidity pattern mining, mint abuse detection, blacklist/fee manipulation signals, ML-inspired scoring models, and how to quantify ERC-20 token scam probability.

A comprehensive guide to designing economically safe ERC-20 tokens using formal invariants and strict permission boundaries. Covers supply caps, fee ceilings, liquidity guarantees, transfer safety, oracle integrity, upgrade control, and economic threat modeling. Focused on real-world DeFi security and robust token design.

This repository contains the Autonolas tokenomics part of the autonolas-v1 protocol.

A deep research study introducing the concept of Economic DNA Repair for smart contracts, designing self-correcting tokenomics that detect anomalies, repair unstable parameters, rebalance incentives, and restore economic equilibrium. Explores adaptive rewards, automated governance, liquidity healing, and resilience in decentralized systems.

Use any AI model, locally or in the cloud, while tracking on-device token usage and collecting token telemetry data.

Agent-based economic and tokenomics simulation in Python with declarative scenarios, deterministic lineage, Monte Carlo runs, and reproducible artifacts.

A deep research study introducing the Gene Drift Hypothesis: a framework explaining how tokenomics mutate across market cycles. Analyzes evolutionary forces, selective pressures, behavioral traits, and economic genes that rise, fall, or mutate through bull/bear phases, shaping token species over time.

A scientific exploration of Metabolic Tokenomics, the framework that models token economies as living metabolic systems. Examines how tokens burn, store, and circulate energy like biological cells, mapping catabolism, anabolism, liquidity flow, yield dynamics, and system health to design resilient, adaptive on-chain ecosystems.

A research-grade exploration of the Tokenomics Ecological Framework, analyzing how tokens behave as predator, prey, parasite, and symbiotic species. Examines ecosystem interactions, evolutionary pressures, species population cycles, and the dynamics of economic predation, mutation, drift, and long-term survival across market cycles.

A deep technical exploration of how malicious smart-contract developers weaponize fee logic in ERC-20 tokens. Covers dynamic tax flipping, hidden sell traps, fee obfuscation, whitelist-based bypasses, liquidity-drain funnels, attack timelines, forensic analysis, mathematical modeling, and ML-powered detection strategies for tax abuse.

A research-grade framework for forecasting tokenomic gene evolution across market cycles. Analyzes historical gene frequencies, models behavioral drift, and predicts future gene expression using interpretable trend and moving-average forecasting. Designed for tokenomics research, risk analysis, and evolutionary cryptoeconomics.