@GitHub_Daily: Using Claude Code for complex projects, a single agent has limited capabilities. Want multiple agents to collaborate and divide tasks, but manually configuring team structures and skill files is too tedious. Recently found Harness, a Claude Code plugin that automatically generates an entire team architecture from a one-sentence description of your project...

Using Claude Code for complex projects, a single agent has limited capabilities. You might want multiple agents to collaborate and divide tasks, but manually configuring team structures and skill files is too cumbersome. Recently, I found this plugin called Harness for Claude Code. Just describe your project in one sentence, and it automatically generates a complete agent team architecture. It comes with 6 built-in team collaboration modes—such as pipeline, parallel processing, expert pool, producer-reviewer, etc.—and can automatically choose the most suitable architecture based on your needs. GitHub: http://github.com/revfactory/harness… The generated output includes agent definition files and skill files that can be placed directly into your project’s .claude directory. The whole process, from domain analysis to team design to validation testing, is completed in six automated steps. The official repository also provides 100 ready-to-use team configuration templates covering deep research, website development, content creation, code review, and more—plug and play. If you want Claude Code to evolve from a “solo operator” into a “team collaboration,” this plugin is worth a try. — # revfactory/harness Source: https://github.com/revfactory/harness # 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 (https://github.com/coleam00/Archon) | | L3 — Meta-Factory / Codex Runtime Port | Same concept, Codex runtime | SaehwanPark/meta-harness (https://github.com/SaehwanPark/meta-harness) | | L2 — Cross-Harness Workflow | Standardize skills/rules/hooks across multiple harnesses | affaan-m/ECC (https://github.com/affaan-m/everything-claude-code) | > 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 ## 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 ## 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 shell /plugin marketplace add revfactory/harness #### Install the plugin shell /plugin install harness@harness-marketplace ### Direct Installation as Global Skill shell # 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 | ### 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 (https://github.com/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 (https://github.com/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 (https://github.com/affaan-m/everything-claude-code) | “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 (https://github.com/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 (https://langchain-ai.github.io/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 (https://github.com/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 (https://github.com/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 - Agent Teams enabled (https://code.claude.com/docs/en/agent-teams): CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 ## 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 (https://github.com/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: - Archon self-definition: clawfit docs/reference-levels.md (https://github.com/hongsw/clawfit/blob/main/docs/reference-levels.md) - Sub-layer declaration: see the Category — Where Harness Sits section above - Archon repo: github.com/coleam00/Archon (https://github.com/coleam00/Archon) 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 (https://github.com/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: - Codex port: github.com/SaehwanPark/meta-harness (https://github.com/SaehwanPark/meta-harness) - Cross-runtime scaffolder: github.com/Gizele1/harness-init (https://github.com/Gizele1/harness-init) ## License Apache 2.0