Best practices for working on the Harness books repo. Use this skill when editing, restructuring, building, or exporting the books under `book1-claude-code/` and `book2-comparing/`, especially for Honkit, print HTML, Pandoc/XeLaTeX PDF export, build cleanup, TOC issues, naming conventions, and keeping source assets separate from generated outputs. --- # Harness Book Best Practice Use this skill for changes inside this repository's book system. ## Scope
Optimize an AI agent's harness for MCP-Atlas benchmark. Use when analyzing execution traces, diagnosing failures, and proposing improved prompts, skills, or harness code.
Add or update a model in the harness model registry. Use when the user wants to add a new AI model, update model pricing, or change default models for a harness.
MoAI — 100개 자기진화 도메인 하네스 AI 전문가. '/moai init'으로 개인화된 하네스를 설치하고, '/moai catalog'로 카탈로그를 조회하고, '/moai status'로 상태를 확인한다. '유튜브 영상 기획', '시장 조사', '계약서 검토', '사업계획서', '여행 계획', '뉴스레터 작성', '세무 상담', '채용 파이프라인', 'ESG 보고서', '데이터 분석' 등 100가지 도메인의 전문가 하네스를 제공한다. 자연어로 도메인 요청 시 자동 감지하여 해당 하네스 레퍼런스를 로딩한다. MoAI, 모아이, harness, 하네스, 전문가 모드, expert mode.
MoAI — 100개 자기진화 도메인 하네스 AI 전문가. '/moai init'으로 개인화된 하네스를 설치하고, '/moai catalog'로 카탈로그를 조회하고, '/moai status'로 상태를 확인한다. '유튜브 영상 기획', '시장 조사', '계약서 검토', '사업계획서', '여행 계획', '뉴스레터 작성', '세무 상담', '채용 파이프라인', 'ESG 보고서', '데이터 분석' 등 100가지 도메인의 전문가 하네스를 제공한다. 자연어로 도메인 요청 시 자동 감지하여 해당 하네스 레퍼런스를 로딩한다. MoAI, 모아이, harness, 하네스, 전문가 모드, expert mode.
- 📁 agents/
- 📁 references/
- 📄 LICENSE.txt
- 📄 SKILL.md
Design a real harness for an agentic system using Claude Code-inspired patterns. Use when the user needs a harness blueprint, request assembly design, execution loop, tool runtime, memory layering, permission model, transcript or recovery strategy, or wants to turn a vague agent idea into a harness-level architecture. Do not use for generic product brainstorming, simple prompt writing, or isolated code generation.
- 📁 data/
- 📁 evals/
- 📁 examples/
- 📄 README.md
- 📄 README.zh.md
- 📄 skill.json
Audit, design, and implement AI agent harnesses for any codebase. A harness is the constraints, feedback loops, and verification systems surrounding AI coding agents — improving it is the highest-leverage way to improve AI code quality. Three modes: Audit (scorecard), Implement (set up components), Design (full strategy). Use whenever the user mentions harness engineering, agent guardrails, AI coding quality, AGENTS.md, CLAUDE.md setup, agent feedback loops, entropy management, AI code review, vibe coding quality, harness audit, harness score, AI slop, agent-first engineering. Also trigger when users want to understand why AI agents produce bad code, make their repo work better with AI agents, set up CI/CD for agent workflows, design verification systems, or scale AI-assisted development. Proactively suggest when discussing AI code drift or controlling AI-generated code quality. --- # Harness Engineering Guide You are a harness engineering consultant. Your job is to audit, design, and implement the environments, constraints, and feedback loops that make AI coding agents work reliably at production scale. **Core Insight**: Agent = Model + Harness. The harness is everything surrounding the model: tool access, context management, verification, error recovery, and state persistence. Changing only the harness (not the model) improved LangChain's agent from 52.8% to 66.5% on Terminal Bench 2.0. ## Pre-Assessment Gate Before running an audit, answer these 5 questions to determine the appropriate audit depth. 1. Is the project expected to live beyond 1 month? 2. Will AI agents modify this codebase going forward? 3. Does the project have (or plan to have) >500 LOC? 4. Has there been at least one instance of AI-generated code causing problems? 5. Is there more than one contributor (human or agent)? | "Yes" Count | Route | What You Get | |-------------|-------|--------------| | **4-5** | **Full Audit** | All 45 items scored across 8 dimensions. Detailed report with improvement