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Version License Claude Code Plugin 6 Architecture Patterns Agent Teams GitHub Stars

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Harness — The Team-Architecture Factory for Claude Code

English | 한국어 | 日本語

Harness is a team-architecture factory for Claude Code. Say "build a harness for this project" (English) or "하네스 구성해줘" (한국어) or "ハーネスを構成して" (日本語), and the plugin turns your domain description into an agent team and the skills they use — picked from six pre-defined team-architecture patterns.

Overview

Harness leverages Claude Code's agent team system to decompose complex tasks into coordinated teams of specialized agents. Say "build a harness for this project" and it automatically generates agent definitions (.claude/agents/) and skills (.claude/skills/) tailored to your domain.

Category — Where Harness Sits

Harness lives at the L3 Meta-Factory layer of the Claude Code ecosystem — the layer that generates other harnesses rather than being one. Inside L3, we pick a specific sub-layer: Team-Architecture Factory.

Layer What it does Neighbors we coexist with
L3 — Meta-Factory / Team-Architecture Factory (us) Domain sentence → agent team + skills, via 6 pre-defined team patterns
L3 — Meta-Factory / Runtime-Configuration Factory Deterministic, repeatable runtime configurations coleam00/Archon
L3 — Meta-Factory / Codex Runtime Port Same concept, Codex runtime SaehwanPark/meta-harness
L2 — Cross-Harness Workflow Standardize skills/rules/hooks across multiple harnesses affaan-m/ECC

Archon generates deterministic runtime configurations. Harness generates team architectures (pipeline, fan-out/fan-in, expert pool, producer-reviewer, supervisor, hierarchical delegation) plus the skills agents use. Different sub-layers of the same L3. Pick Archon for runtime determinism, Harness for team architecture, or combine them.

Star History

Star History Chart

Key Features

  • Agent Team Design — 6 architectural patterns: Pipeline, Fan-out/Fan-in, Expert Pool, Producer-Reviewer, Supervisor, and Hierarchical Delegation
  • Skill Generation — Auto-generates skills with Progressive Disclosure for efficient context management
  • Orchestration — Inter-agent data passing, error handling, and team coordination protocols
  • Validation — Trigger verification, dry-run testing, and with-skill vs without-skill comparison tests

Harness Evolution Mechanism

The harness evolution mechanism feeds deltas (what worked / what didn't) back into the factory, so the next generation is measurably better. When a generated harness is used in a real project, the /harness:evolve skill captures the delta between the initial architecture and the shipped one, and feeds it back into the factory so the next generation for a similar domain starts closer to the shipped state.

Initial harness ──▶ Real project use ──▶ Shipped harness
                                              │
                                              ▼ (delta capture via /harness:evolve)
                                        ┌───────────────┐
                                        │  Factory      │◀── better next-gen draft
                                        └───────────────┘

We call this the Harness Evolution Mechanism (KR: 하네스 진화 메커니즘; JA: ハーネス進化メカニズム).

Workflow

Phase 1: Domain Analysis
    ↓
Phase 2: Team Architecture Design (Agent Teams vs Subagents)
    ↓
Phase 3: Agent Definition Generation (.claude/agents/)
    ↓
Phase 4: Skill Generation (.claude/skills/)
    ↓
Phase 5: Integration & Orchestration
    ↓
Phase 6: Validation & Testing

Installation

Via Marketplace

Add the marketplace

/plugin marketplace add revfactory/harness

Install the plugin

/plugin install harness@harness

Direct Installation as Global Skill

# Copy the skills directory to ~/.claude/skills/harness/
cp -r skills/harness ~/.claude/skills/harness

Plugin Structure

harness/
├── .claude-plugin/
│   └── plugin.json                 # Plugin manifest
├── skills/
│   └── harness/
│       ├── SKILL.md                # Main skill definition (6-Phase workflow)
│       └── references/
│           ├── agent-design-patterns.md   # 6 architectural patterns
│           ├── orchestrator-template.md   # Team/subagent orchestrator templates
│           ├── team-examples.md           # 5 real-world team configurations
│           ├── skill-writing-guide.md     # Skill authoring guide
│           ├── skill-testing-guide.md     # Testing & evaluation methodology
│           └── qa-agent-guide.md          # QA agent integration guide
└── README.md

Usage

Trigger in Claude Code with prompts like:

Build a harness for this project
Design an agent team for this domain
Set up a harness

Execution Modes

Mode Description Recommended For
Agent Teams (default) TeamCreate + SendMessage + TaskCreate 2+ agents requiring collaboration
Subagents Direct Agent tool invocation One-off tasks, no inter-agent communication needed

Harness Agent Team

Architecture Patterns

Pattern Description
Pipeline Sequential dependent tasks
Fan-out/Fan-in Parallel independent tasks
Expert Pool Context-dependent selective invocation
Producer-Reviewer Generation followed by quality review
Supervisor Central agent with dynamic task distribution
Hierarchical Delegation Top-down recursive delegation

Output

Files generated by Harness:

your-project/
├── .claude/
│   ├── agents/          # Agent definition files
│   │   ├── analyst.md
│   │   ├── builder.md
│   │   └── qa.md
│   └── skills/          # Skill files
│       ├── analyze/
│       │   └── SKILL.md
│       └── build/
│           ├── SKILL.md
│           └── references/

Use Cases — Try These Prompts

Copy any prompt below into Claude Code after installing Harness:

Deep Research

Build a harness for deep research. I need an agent team that can investigate
any topic from multiple angles — web search, academic sources, community
sentiment — then cross-validate findings and produce a comprehensive report.

Website Development

Build a harness for full-stack website development. The team should handle
design, frontend (React/Next.js), backend (API), and QA testing in a
coordinated pipeline from wireframe to deployment.

Webtoon / Comic Production

Build a harness for webtoon episode production. I need agents for story
writing, character design prompts, panel layout planning, and dialogue
editing. They should review each other's work for style consistency.

YouTube Content Planning

Build a harness for YouTube content creation. The team should research
trending topics, write scripts, optimize titles/tags for SEO, and plan
thumbnail concepts — all coordinated by a supervisor agent.

Code Review & Refactoring

Build a harness for comprehensive code review. I want parallel agents
checking architecture, security vulnerabilities, performance bottlenecks,
and code style — then merging all findings into a single report.

Technical Documentation

Build a harness that generates API documentation from this codebase.
Agents should analyze endpoints, write descriptions, generate usage
examples, and review for completeness.

Data Pipeline Design

Build a harness for designing data pipelines. I need agents for schema
design, ETL logic, data validation rules, and monitoring setup that
delegate sub-tasks hierarchically.

Marketing Campaign

Build a harness for marketing campaign creation. The team should research
the target market, write ad copy, design visual concepts, and set up
A/B test plans with iterative quality review.

Coexistence — Harness and Neighbors

Harness is not alone in the Claude Code / agent-framework ecosystem. The following repos live in adjacent layers; each is described in a parallel "X is …, Harness is …" form so you can pick the one that fits your need or combine several.

Repo Their position Relationship to Harness
coleam00/Archon "harness builder" — deterministic, repeatable runtime configurations Same L3, neighbor sub-layer. Archon is a Runtime-Configuration Factory, Harness is a Team-Architecture Factory. Pick Archon for runtime determinism, Harness for team architecture, or combine them.
SaehwanPark/meta-harness Codex port of the same concept Same L3, different runtime. Use Harness on Claude Code, meta-harness on Codex.
affaan-m/ECC "Agent harness performance & workflow layer" (sits on top of existing harnesses) Different layer. ECC is a standardization layer across harnesses; Harness is a factory that generates harnesses. Serial combination possible.
wshobson/agents Subagent / skill catalog (182 agents, 149 skills) Factory ↔ parts supply. wshobson is a catalog to shop from; Harness designs the team. Absorb wshobson entries as parts inside a Harness-generated team.
LangGraph State-graph orchestration, LLM-agnostic Different track. LangGraph is for long-running, state-recoverable orchestration; Harness is for fast Claude-Code-native team design.

Built with Harness

Harness 100

revfactory/harness-100 — 100 production-ready agent team harnesses across 10 domains, available in both English and Korean (200 packages total). Each harness ships with 4-5 specialist agents, an orchestrator skill, and domain-specific skills — all generated by this plugin. 1,808 markdown files covering content creation, software development, data/AI, business strategy, education, legal, health, and more.

Research: A/B Testing Harness Effectiveness

revfactory/claude-code-harness — A controlled experiment across 15 software engineering tasks measuring the impact of structured pre-configuration on LLM code agent output quality.

Metric Without Harness With Harness Improvement
Average Quality Score 49.5 79.3 +60%
Win Rate 100% (15/15)
Output Variance -32%

Key finding: effectiveness scales with task complexity — the harder the task, the greater the improvement (+23.8 Basic, +29.6 Advanced, +36.2 Expert).

Exact phrasing to use everywhere: +60% avg quality (49.5 → 79.3), 15/15 win-rate, −32% variance (n=15, author-measured A/B, third-party replications pending).

Full paper: Hwang, M. (2026). Harness: Structured Pre-Configuration for Enhancing LLM Code Agent Output Quality.

Requirements

FAQ

Q1. Isn't "+60%" oversold?

A. The +60% figure comes from an author-measured A/B (n=15, 15 tasks, measured on the sister repo claude-code-harness). Every citation in this repo pairs the number with the disclosure "n=15, author-measured, third-party replications pending" in the same sentence. For adoption decisions, we recommend running a 2–4 week internal pilot and measuring your own numbers.

Evidence:

  • Author A/B: revfactory/claude-code-harness
  • Paper: Hwang, M. (2026). Harness: Structured Pre-Configuration for Enhancing LLM Code Agent Output Quality
Q2. Why "harness factory" and not "harness builder"? Isn't this competing with Archon?

A. Archon generates deterministic runtime configurations — it's a Runtime-Configuration Factory. Harness generates agent team architectures (team structure, message protocols, review gates) — it's a Team-Architecture Factory. They are neighbor sub-layers of the same L3 Meta-Factory and serve different needs. Pick Archon for runtime determinism, Harness for team-architecture patterns, or combine them (design architecture with Harness → deploy runtime with Archon).

Evidence:

Q3. Isn't "Claude Code only" too narrow? What about Gemini/Codex?

A. Currently the official runtime is Claude Code only. A Codex port of the same concept — SaehwanPark/meta-harness — is already public, so Codex teams can start there. Harness chose "Claude-Code-native, deep" over "multi-runtime, shallow"; cross-runtime collaboration with sibling repos (meta-harness, harness-init, OpenRig) is on the roadmap.

Evidence:

License

Apache 2.0

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A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.

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