harness — Claude Code plugin: builds an agent team for your project
Describe your project in one sentence and the plugin turns it into a team of agents plus the skills they use. Useful when a task outgrows a single agent.
/plugin marketplace add anthropics/claude-plugins-community
/plugin install harness@claude-communityWhat harness does
harness is a team-architecture factory for Claude. It walks seven phases: audit of the existing setup, domain analysis, execution-mode choice, agent definitions in .claude/agents/, skill generation in .claude/skills/, orchestration with a CLAUDE.md pointer, then verification and maintenance. Everything it writes is plain files you can read and edit.
The execution mode follows the shape of the control flow, not team size. Deterministic fan-outs and verification loops become workflow scripts, long-lived specialists become named agents with SendMessage and shared task lists, and one-shot parallel work goes to sub-agents. Model tier is picked per agent, so blanket pins are off the table.
Version 2 targets the current runtime. The experimental CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 flag is gone, and v1 artifacts such as TeamCreate are detected in phase 0 with a mechanical migration offered. No environment variables are needed to install.
What it helps with
- split a large task into a team of agents with distinct roles
- generate skills tailored to a project's domain
- pick an execution mode that matches the control flow
- migrate an agent setup from v1 to the current runtime
- run an A/B check of a skill with and without it
Example prompts for the agent
- build a harness for this project
- design an agent team for payment processing
- evolve the harness with this feedback
How to install harness
Plugin marketplace
/plugin marketplace add anthropics/claude-plugins-community/plugin install harness@claude-communityStep by step, with commands for each platform: Claude Code plugins: marketplaces, installing, and building your own
Questions about harness
How do I install harness in Claude?
Through the marketplace: run /plugin marketplace add anthropics/claude-plugins-community, then /plugin install harness@claude-community.
What does harness do?
It turns a domain description into an agent team and the skills they use: definitions in .claude/agents/, skills in .claude/skills/, plus orchestration and a CLAUDE.md pointer.
How is v2 different from v1?
It drops the experimental flag and the TeamCreate API, adds three execution modes, per-agent model selection and a working /harness:evolve command. Old artifacts are detected and migrated.
Source text
SKILL.md · Apache-2.0
<p align="center">
<img src="https://img.shields.io/badge/Version-2.1.0-brightgreen.svg" alt="Version">
<a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License"></a>
<img src="https://img.shields.io/badge/Claude_Code-Plugin-purple.svg" alt="Claude Code Plugin">
<img src="https://img.shields.io/badge/Execution_Modes-3-teal.svg" alt="3 Execution Modes">
<img src="https://img.shields.io/badge/Patterns-6+Quality-orange.svg" alt="Patterns">
</p>
<p align="center">
<a href="https://revfactory.github.io/harness-animation/">
<img src="harness_reel_en.gif" alt="Harness in 15 seconds: one request becomes an agent team" width="800">
</a>
<br>
<sub>15-second motion reel · <a href="https://revfactory.github.io/harness-animation/">Watch the full 2-minute interactive walkthrough (Korean) →</a></sub>
</p>
# Harness v2 — The Team-Architecture Factory for Claude Code
**English** | [한국어](README_KO.md)
> **Harness is a team-architecture factory for Claude Code.** One sentence — **"build a harness for this project"** · **"하네스 구성해줘"** — and the plugin turns your domain description into an agent team and the skills they use.
## What's new in v2
v2 is a ground-up rebuild for the current Claude Code multi-agent runtime:
- **Three native execution modes.** v1 knew two modes built on the experimental `TeamCreate` API, which no longer exists. v2 targets what actually ships today:
1. **Workflow orchestration** — deterministic scripts (`pipeline()` / `parallel()` / schemas / budgets) for fan-outs, verification loops, and large-scale runs
2. **Persistent agent collaboration** — named agents + `SendMessage` + shared task lists, with context retained across turns
3. **Sub-agent delegation** — lightweight one-shot parallel dispatch
- **Workflow-native quality patterns.** Adversarial verification, judge panels, loop-until-dry, multi-modal sweeps, completeness critics — codified so generated harnesses filter out plausible-but-wrong output.
- **No experimental flags.** The `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1` dependency is gone entirely.
- **Sane model policy.** v1 pinned every agent to `model: "opus"`. v2 selects a tier per agent — fable / opus / sonnet — based on the task's complexity, duration, autonomy, and latency needs, and forbids unjustified blanket pins.
- **`/harness:evolve` actually ships.** The evolution mechanism v1 only documented is now a real skill: it captures the delta between your initial and current harness, generalizes feedback, and feeds it back into agents/skills/orchestrators.
- **v1 migration built in.** The factory detects v1 artifacts (`TeamCreate`, `TeamDelete`, experimental flags) and offers a mechanical migration path.
## Core features
- **Agent team design** — six architecture patterns (Pipeline, Fan-out/Fan-in, Expert Pool, Producer-Reviewer, Supervisor, Hierarchical Delegation), each mapped to its best v2 execution mode
- **Skill generation** — context-efficient skills via Progressive Disclosure
- **Orchestration** — data-passing protocols (structured schemas, files, messages, tasks), error handling, resume support
- **Verification** — trigger evals, dry runs, with-skill vs. without-skill A/B testing (optionally as a workflow itself)
- **Evolution** — `/harness:evolve` turns usage feedback into measurable next-generation improvements
## Workflow
```
Phase 0: Audit existing harness (new / extend / maintain — v1 artifacts detected here)
Phase 1: Domain analysis (incl. control-flow shape of the work)
Phase 2: Execution mode & team architecture design
Phase 3: Agent definitions (.claude/agents/)
Phase 4: Skill generation (.claude/skills/)
Phase 5: Orchestration & CLAUDE.md pointer
Phase 6: Verification & testing
Phase 7: Maintenance — evolution via /harness:evolve
```
## Install
### Via marketplace
```shell
/plugin marketplace add revfactory/harness
/plugin install harness@harness-marketplace
```
### As global skills
```shell
cp -r skills/harness ~/.claude/skills/harness
cp -r skills/evolve ~/.claude/skills/harness-evolve
```
No environment variables or experimental flags required.
## Usage
```
하네스 구성해줘
build a harness for this project
design an agent team for <domain>
```
After using a generated harness:
```
하네스 회고해줘 / evolve the harness with this feedback
```
### Choosing an execution mode
| Mode | Primitive | When |
|------|-----------|------|
| **Workflow orchestration** | `Workflow` scripts | Control flow is deterministic: enumerable fan-outs, verification loops, large scale, structured outputs |
| **Persistent agents** | `Agent(name:)` + `SendMessage` + tasks | Long-lived specialists that keep context; iterative feedback and negotiation |
| **Sub-agent delegation** | one-shot `Agent` calls | Fire-and-forget parallel work; results only |
The factory picks the mode from the **shape of the control flow**, not from team size — and mixes modes per phase when that fits better.
## Generated artifacts
```
your-project/
├── .claude/
│ ├── agents/ # agent definitions (who)
│ │ ├── analyst.md
│ │ ├── builder.md
│ │ └── qa.md
│ └── skills/ # skills (how) + one orchestrator (who-when-in-what-order)
│ ├── analyze/SKILL.md
│ └── build/SKILL.md
└── CLAUDE.md # minimal pointer: trigger rule + change history
```
## Migrating from v1
See [docs/migration-v1-to-v2.md](docs/migration-v1-to-v2.md). Summary: remove `TeamCreate`/`TeamDelete`/broadcast/flag references, convert fan-outs to Workflow scripts, rewrite remaining collaboration with named agents + `SendMessage`, drop blanket `model: "opus"` pins. The factory automates this when it detects v1 artifacts (Phase 0).
## Prior results (v1)
A controlled A/B on 15 software-engineering tasks measured the effect of structured pre-configuration on LLM code-agent output quality: mean quality 49.5 → 79.3 (+60%), 15/15 win rate, −32% output variance (n=15, author-run, see [revfactory/claude-code-harness](https://github.com/revfactory/claude-code-harness)). Treat these as author-measured numbers; run your own pilot for adoption decisions.
## License
Apache 2.0
© revfactory · Apache-2.0 · revfactory/harness