hlxstc-create/challenge-project-methodology

README excerpt

Challenge Project A battle-tested methodology for high-difficulty AI-agent projects — distilled from real production practice. Scale by complexity, verify by evidence, evolve the harness. [English] 简体中文 Table of Contents - Why - Quick Start - Core Mechanisms - Versions - Platform Adaptation - Credits - Contributing - License Why - 能力在装具，不在模型 — Agent = Model + Harness ; the main lever is the harness (rules, checklists, prompts, flows), not the model. - loop on evidence, not confidence — terminate with tests/evidence, never "looks right". - 该轻则轻，该重则重 — L0-L3 grading keeps token efficiency optimal. - DeepSeek Harness efficiency — grade every task (L0-L3) so tokens go where they matter; terminate on evidence instead of guesswork; break retry loops (≤2 attempts) before they burn context; evolve rules after each delivery, so recurring work costs a fraction (up to 6-10x fewer tokens). v2.0 fuses three frontier papers on harness engineering: 1. Harness Engineering (David Daniel, 2026-06) → three separation modes (planner/executor, writer/reviewer, initializer/coder) 2. The Last Harness You'll Ever Build (arXiv:2604.21003) → Agent = Model + Harness, Harness Evolution Loop 3. The Harness Lay…

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