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harness-designing-plugin

Harness Designing Plugin helps design teams turn their scattered AI setup — Notion prompts, Figma comments, AGENTS.md rules, chat histories

Open source Repository Open in the app JSON README (API)

About

Harness Designing Plugin helps design teams turn their scattered AI setup — Notion prompts, Figma comments, AGENTS.md rules, chat histories — into a five-layer design harness that compounds across sessions and rotations. Four skills walk you through the assembly: • /hd:learn — Q&A about the five-layer concept (Context Engineering, Skill Curation, Workflow Orchestration, Rubric Setting, Knowledge Compounding) • /hd:setup — detects existing harness artifacts, pre-analyzes all five layers in parallel (5× harness-auditor + rubric-recommender), then walks you through link / critique / scaffold / skip per layer • /hd:maintain — captures lessons and promotes them to team rules in AGENTS.md with SHA-256 plan-hash proof-of-consent • /hd:review — audits harness health in a 2-batch parallel dispatch (5 layer-specialist agents + 2–3 context agents); critiques harness artifacts against quality rubrics Ships 9 sub-agents and 14 starter rubrics (distilled from pbakaus/impeccable, Nielsen's 10 heurist

Details

Kind
Plugins
Topic
Government & public data
Publisher
billogic
Origin
marketplace
Category
ferramentas
Stars
5
Last push
2026-08-24T19:49:41Z
Repository state
ativo
Language
Python
License
MIT
Added
2026-08-30 01:48:58
Updated
2026-08-30 01:48:58
Origin id
billogic/harness-designing-plugin/harness-designing-plugin

README

![Harness Designing banner — stop chasing design tools, start building a design harness](assets/banner.png)

# Harness Designing

**A plug-in that turns your team's scattered AI usage into a design practice that compounds.**

Four skills. Five layers. One harness your whole team inherits—across Notion, Figma, design.md, and every chat thread.

Works with [Claude](https://claude.com/claude-code), [Codex](https://github.com/openai/codex), [Cursor](https://cursor.com), and other agentic coding tools. [Install →](#installation)

📖 **Read the article first** → [*Stop Chasing Design Tools. Start Building a Design Harness*](https://rexandduckie.substack.com/p/stop-chasing-design-tools-start-building) by [Bill Guo](https://www.linkedin.com/in/boyuang/). The argument lives there; this README is the implementation.

![Stop chasing design tools. Start building a design harness.](assets/meme%200%20banner.png)

> *"Tools lower the floor. Taste sets the ceiling. Your harness is the ladder."*
> — [Bill Guo](https://www.linkedin.com/in/boyuang/), [*Stop Chasing Design Tools. Start Building a Design Harness*](https://rexandduckie.substack.com/p/stop-chasing-design-tools-start-building)

## Thesis

AI keeps lowering the floor for design output, and every new tool resets the practice you built around the last one. For teams with standards already in place, that treadmill is the real cost of AI.

A design harness is the layer your team owns across tools. Five layers—context, skills, workflows, evaluation, knowledge—version-controlled in your repo, inherited by every AI-assisted task. Tools come and go. The harness compounds.

```
Agent = Model + Harness
```

```
Design Harness = Context + Skills + Orchestration + Evaluations + Compounding
```

![The Design Harness — a team-owned stack that makes AI work reusable, reviewable, and compounding. Floor: generic AI output. Ceiling: design team's full potential. Five rungs: Context Engineering, Skill Curation, Workflow Orchestration, Evaluation Design, Knowledge Compounding.](assets/design%20harness.png)

| Layer | What lives here | How it connects |
|---|---|---|
| **1. Context Engineering** | Product facts, users, brand voice, design tokens, conventions | Loaded first on every task. Every other layer reads from it. |
| **2. Skill Curation** | Repeatable jobs (research, plan, prototype, review, compound) | Draws from Context. Invokes Rubrics at gates. Writes to Knowledge. |
| **3. Workflow Orchestration** | How skills compose—sequences, handoffs, gates | Emerges from how Skills dispatch agents. |
| **4. Evaluation Design** | Quality bars made checkable—a11y, design-system, typography, telemetry, i18n | Applied by Skills at workflow gates through rubrics. |
| **5. Knowledge Compounding** | Lessons, decisions, preferences, changelog | Captured by every skill. Recurring patterns promote to Context rules. |

**At each layer, four choices:**

- **scaffold** — point at what already exists, wrap structure around it
- **review** — evaluate it against a rubric, flag what could improve
- **create** — start from scratch with seeded prompts
- **skip** — leave this layer for later

## Commands

### [`/hd:learn`](skills/hd-learn/SKILL.md) — ask about the concept

Read-only Q&A about any layer, memory type, or decision in the framework.

Ten reference files back the answers—one per layer, plus glossary, FAQ, and memory taxonomy. Article sections cited when the corpus is configured.

**Try:**

- *"What's the difference between Layer 1 and Layer 5?"*
- *"When should I scaffold vs. create at Layer 1?"*
- *"Walk me through the five layers for a team just starting out."*

### [`/hd:setup`](skills/hd-setup/SKILL.md) — walk your repo, layer by layer

Detects existing harness artifacts (`.agent/`, `.claude/`, `docs/context/`, etc.). Analyzes all five layers in parallel up front. Walks each layer with a **preview-before-write gate**.

Per layer: **scaffold** · **review** · **create** · **skip**.

When scaffolding a greenfield repo, it proposes this starting structure:

```
<repo-root>/
├── AGENTS.md                   # always-loaded rules + harness map + agent persona
├── hd-config.md                # machine-parseable config
│
├── docs/
│   ├── context/                # L1 — what's always true
│   │   ├── product/            # one-pager, users, journeys, capabilities, metrics
│   │   ├── engineering/        # stack, data, API, deployment, dev env, security
│   │   ├── design-system/      # styles · foundations · components
│   │   └── conventions/        # repo map + team norms
│   │
│   ├── rubrics/                # L4 — how we judge "good"
│   └── knowledge/              # L5 — changelog, decisions, ideations, preferences, lessons
│
├── skills/                     # L2 — repeatable jobs
└── agents/                     # L3 emerges from skills ↔ agents dispatch
```

> **Starting template, not a contract.** Rename folders, skip layers, add your own. The plug-in audits what exists, suggests what's missing, respects what you built (additive-only by default). Full spec: [`standard-harness-structure.md`](skills/hd-setup/references/standard-harness-structure.md).

### [`/hd:maintain`](skills/hd-maintain/SKILL.md) — capture lessons, promote to rules

**Capture.** When a decision, surprise, or recurring pattern is worth remembering. One dated file per event.

**Propose.** When the same pattern shows up three or more times, `rule-propose` scores it and suggests a new rule for `AGENTS.md`.

**Adopt.** Rule adoption requires SHA-256 plan-hash proof-of-consent. Rules never land by accident.

**Try:**

- *"Capture a lesson: our AntD buttons don't work with dark-mode tokens; reverted to custom overrides."*
- *"Propose a rule: we've had three lessons about dark-mode token drift this month."*

### [`/hd:review`](skills/hd-review/SKILL.md) — full or targeted review

**Full review** across all five layers:

- Writes a dated report to `docs/knowledge/reviews/<date>-harness-review.md`
- Emits a chat summary with ASCII health bars, priorities table, cross-layer signals, a **Proposed revision** file-tree diff, and a staleness check against any prior review
- Pair with `/hd:setup --from-review <path>` to apply findings as concrete writes

**Targeted review** of one layer, file, or work item against your team's rubrics.

**17 starter rubrics ship with the plug-in.** Copy any into `docs/rubrics/<name>.md` and customize:

| Category | Rubrics |
|---|---|
| **Craft** | `accessibility-wcag-aa`, `design-system-compliance`, `component-budget`, `interaction-states`, `heuristic-evaluation` |
| **Visual** | `typography`, `color-and-contrast`, `spatial-design`, `motion-design` |
| **Communication** | `ux-writing`, `responsive-design` |
| **Domain-specific** | `telemetry-display`, `i18n-cjk` |
| **Harness self-checks** | `skill-quality`, `agent-spec-quality`, `plan-quality`, `lesson-quality` |

Each rubric carries a `## Scope & Grounding` block—personas, user stories, scenarios, anti-scenarios—with source citation.

Six rubrics ship in the YAML-criteria schema (machine-queryable). The other eleven are prose-only reference material; `/hd:setup` walks the YAML migration when you adopt one. See [`rubric-yaml-schema.md`](skills/hd-review/references/rubric-yaml-schema.md) for the migrate-on-adopt policy.

> **The plug-in maintains the library. Your AI applies it** to your design work.

## Install

### Claude Code

```text
/plugin marketplace add BilLogic/harness-designing-plugin
/plugin install harness-designing
```

### Cursor

In Cursor Agent chat:

```text
/add-plugin harness-designing
```

Or search "harness designing" in the plug-in marketplace.

### Codex

Two steps — register the marketplace, then install through Codex's TUI.

1. **Register the marketplace:**

   ```bash
   codex plugin marketplace add BilLogic/harness-designing-plugin
   ```

2. **Install through the TUI:** launch `codex`, run `/plugins`, find the **harness-designing** marketplace, select **harness-designing**, and choose **Install**. Restart Codex when it finishes. Codex's CLI doesn't have a subcommand for installing a plug-in from an added marketplace yet—the `/plugins` TUI is the only path.

> **Heads up:** Codex's plug-in spec doesn't register custom sub-agents yet, so our 10 sub-agents only dispatch via the Task tool when the host exposes it. On Codex CLI without Task, `/hd:review` runs inline serial (~1–2 min) instead of parallel (~30s). Same output.

### GitHub Copilot

For **VS Code Copilot Agent Plugins**:

1. Run `Chat: Install Plugin from Source` from the VS Code command palette
2. Use `BilLogic/harness-designing-plugin` for the repo
3. Select `harness-designing` when VS Code lists the plug-ins in this repository

For **Copilot CLI**:

Inside Copilot CLI:

```text
/plugin marketplace add BilLogic/harness-designing-plugin
/plugin install harness-designing@harness-designing-plugin
```

From a shell with the `copilot` binary:

```bash
copilot plugin marketplace add BilLogic/harness-designing-plugin
copilot plugin install harness-designing@harness-designing-plugin
```

Copilot CLI reads the same Claude Code-compatible manifest we ship, so no separate install step is needed.

### Factory Droid

From a shell with the `droid` binary:

```bash
droid plugin marketplace add https://github.com/BilLogic/harness-designing-plugin
droid plugin install harness-designing@harness-designing-plugin
```

Droid uses `plugin@marketplace` IDs — `harness-designing` is the plug-in, `harness-designing-plugin` is the marketplace name. Droid reads our Claude Code-compatible manifest and translates the format on install.

### Qwen Code

```bash
qwen extensions install BilLogic/harness-designing-plugin:harness-designing
```

Qwen Code reads the same Claude Code-compatible manifest from GitHub and converts the format during install.

### OpenCode, Pi, Gemini, and Kiro

These hosts don't read Claude Code-compatible manifests yet. Manual install until host support lands:

1. Clone the repo to a stable location:

   ```bash
   git clone https://github.com/BilLogic/harness-designing-plugin ~/plugins/harness-designing
   ```

2. Point your host's skill-loader at `~/plugins/harness-designing/skills/`, or copy / symlink the four skill directories (`hd-learn`, `hd-setup`, `hd-maintain`, `hd-review`) into the path your host expects.

The four `SKILL.md` files are host-agnostic markdown — `/hd:*` invocations work wherever your host loads them. Sub-agent dispatch via the Task tool needs explicit host support; without it, skills run inline serial (same output, slower wall time).

## Credits

**The article**—[Bill Guo's](https://www.linkedin.com/in/boyuang/) [*Stop Chasing Design Tools. Start Building a Design Harness*](https://rexandduckie.substack.com/p/stop-chasing-design-tools-start-building). The thesis, the five-layer frame, and the memory taxonomy all originate there. This plug-in is the starter kit.

**Harness vocabulary + anatomy (primary inspiration)**—LangChain: [*The Anatomy of an Agent Harness*](https://blog.langchain.com/the-anatomy-of-an-agent-harness/) by [Vivek Trivedy](https://x.com/Vtrivedy10) and [*Your Harness, Your Memory*](https://blog.langchain.com/your-harness-your-memory/) by [Harrison Chase](https://x.com/hwchase17). The noun "harness," the memory-typology framing, and the ownership argument come from here—the vocabulary and concept lineage that made a design-focused harness legible in the first place.

**Compounding practice + plug-in pattern**—[compound-engineering-plugin](https://github.com/EveryInc/compound-engineering-plugin) by [Kieran Klaassen](https://twitter.com/kieranklaassen) and the [Every](https://every.to) team, with their companion essay [*Compound Engineering*](https://every.to/guides/compound-engineering). Heavy user—their lesson → rule compounding loop inspired the design-focused compounding we wire into the Workflow Orchestration layer. The structural model (`plugin.json` + skills as commands + agents as categorized sub-agents + plan-then-work workflow) is also lifted from their work.

**Context engineering + harness design for long-running apps**—Anthropic: [*Effective Context Engineering for AI Agents*](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents) by [Prithvi Rajasekaran](https://x.com/rgb_prithvi), [Ethan Dixon](https://www.linkedin.com/in/eltd/), [Carly Ryan](https://www.linkedin.com/in/carly-ryan-2565b3154/), and [Jeremy Hadfield](https://x.com/jerhadf) of the Applied AI team; [*Harness Design for Long-Running Apps*](https://www.anthropic.com/engineering/harness-design-long-running-apps) by Prithvi Rajasekaran (Labs team); [*Effective Harnesses for Long-Running Agents*](https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents) by [Justin Young](https://www.linkedin.com/in/jyoung127) with contributions from David Hershey, Prithvi Rajasekaran, Jeremy Hadfield, Naia Bouscal, Michael Tingley, Jesse Mu, Jake Eaton, Marius Buleandara, Maggie Vo, Pedram Navid, Nadine Yasser, and Alex Notov (Claude Code + code RL teams); [*Authoring Skills for Claude*](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices); and the [Complete Guide to Building Skills for Claude](https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf). Attention-budget and progressive-disclosure patterns from these.

**Rubric source material**
- [pbakaus/impeccable](https://github.com/pbakaus/impeccable) by [Paul Bakaus](https://twitter.com/paulbakaus)—typography, color-and-contrast, spatial-design, motion-design, ux-writing, responsive-design
- [Nielsen Norman Group](https://twitter.com/NNgroup)—[Nielsen's 10 Usability Heuristics](https://www.nngroup.com/articles/ten-usability-heuristics/) by [Jakob Nielsen](https://twitter.com/JakobNielsen) → `heuristic-evaluation`
- [Material Design 3](https://m3.material.io)—Google → `design-system-compliance`, `interaction-states`
- [Fluent 2](https://fluent2.microsoft.design)—Microsoft → `accessibility-wcag-aa`, `ux-writing`

**Adjacent work**—[*Designer's Guide to Context Engineering with AI IDEs*](https://productpower.substack.com/p/the-designers-guide-to-context-engineering) by [Samet Özkale](https://twitter.com/sametozkale) covers context engineering for designers; this plug-in extends to all five layers.

**Working implementation**—[BilLogic/plus-uno](https://github.com/BilLogic/plus-uno) is the source repo this plug-in was distilled from: a production design harness running across a rotating ~15-designer team, used daily for prototyping, design-system work, and AI-assisted critique. It is where the five-layer structure (context, skills, workflows, evaluation, knowledge) was first stress-tested across real projects, real reviews, and real handoffs before being templated into the starter scaffolds shipped here. Read it as the "fully populated" reference for what each layer can grow into once a team has been compounding lessons for a while.

## License

MIT—see [LICENSE](./LICENSE).

![Me watching the harness survive the next tool launch.](assets/meme%203.png)

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