Designer Skill MCP

Plug-and-play MCP. UI superpowers for your agent.

Setup · How it works · References · Tools · Development

Setup

Paste into your agent (Claude Code, Codex, Cursor, any MCP client). It installs the skill, wires the MCP and verifies the tools:

Add designer-skill alongside Niblet Designer UI. The designer core is keyless: it routes requests, loads guidance and runs supplemental static checks. Niblet optionally supplies real screens and licensed materials; the host owns implementation and rendered verification.

1. Install or refresh the skill into the user skill directory (not this project):

npx skills add PyModel/designer-skill --skill designer-skill -g -y

1. Add the local MCP using this client's native MCP configuration, in the user-level (not project-level) config:

Name: designer-skill Transport: stdio Command: npx Args: -y @pymodel/designer-skill-mcp@latest

No API key is needed. Do not add one.

1. Verify: list the designer-skill server's tools and confirm get_preflight_brief, dispatch_intent, review_and_gate are present. Do not run a sample check.

When setup is complete, confirm the skill is installed and the three named tools are exposed. On UI work: call get_preflight_brief, use dispatch_intent and load only relevant guidance. If an unresolved visual question warrants retrieval, use the separately configured niblet server's discovered tools. Prefer its image content for inspection; designer-skill's catalogue wrappers return metadata or routing guidance only. Run review_and_gate as supplemental static evidence, then perform the required rendered, functional and accessibility checks in the host. Never treat static success as UI PASS. Preserve audit/plan scope. Continue an active authorized task; otherwise report designer-skill ready, and report Niblet paired only if its tools were actually observed.

No Niblet? Continue from local product evidence; catalogue retrieval is optional.

Or pick one:

Canonical MCP config (mcp.json):

{ "mcpServers": { "designer-skill": { "command": "npx", "args": ["-y", "@pymodel/designer-skill-mcp@latest"] } } }

@latest tracks npm; teams pin @pymodel/designer-skill-mcp@0.22.0. Plugin skill content updates separately (/plugin update …). MCP registry name: io.github.PyModel/designer-skill-mcp. Requires Node 22+.

Per-client config (VS Code, Codex TOML, Kilo, Open Code, Claude Desktop, Pythinker, Pi)

VS Code .vscode/mcp.json (1.99+):

{ "servers": { "designer-skill": { "type": "stdio", "command": "npx", "args": ["-y", "@pymodel/designer-skill-mcp"] } } }

Codex CLI ~/.codex/config.toml:

[mcp_servers.designer-skill]

command = "npx" args = ["-y", "@pymodel/designer-skill-mcp"]

Open Code opencode.json:

{ "mcp": { "designer-skill": { "type": "local", "command": ["npx", "-y", "@pymodel/designer-skill-mcp"] } } }

Claude Desktop, Cursor (`.cursor/mcp.json`), Kilo Code (`mcp_settings.json`), Pythinker (`~/.pythinker/mcp.json`): the canonical mcpServers JSON above. Pythinker verify: pythinker mcp test designer-skill (guide).

Pi: the same JSON, or register the skill natively: { "skills": [{ "path": "/path/to/skills/designer-skill/SKILL.md" }] }

Local checkout: replace npx with "command": "node", "args": ["/abs/path/to/designer-skill-mcp/dist/index.js"].

How it works

flowchart LR

A[Prompt] --> B[get_preflight_brief] B --> C[dispatch_intent] C --> D[get_reference] D --> E[Build / polish UI] E --> F[review_and_gate] F -->|FAIL: fix| E F -->|static checks pass| G[Rendered checks by the host] classDef start fill:#f8fafc,stroke:#94a3b8,color:#18181b classDef route fill:#eff6ff,stroke:#3b82f6,color:#1e3a8a classDef know fill:#faf5ff,stroke:#7c3aed,color:#4c1d95 classDef work fill:#fff7ed,stroke:#e87a3d,color:#7c2d12 classDef gate fill:#ecfdf5,stroke:#10b981,color:#065f46 classDef host fill:#fff1f2,stroke:#e11d48,color:#881337 class A start class B,C route class D know class E work class F gate class G host

The gate is static only: overall status is FAIL or NOT_VERIFIED, never a rendered-readiness pass. Rendered, accessibility and performance checks stay NOT_RUN until the host supplies evidence.

Niblet ecosystem

Discover tools per server: the same find_ui_references name on designer-skill is a text-only REST wrapper, not Niblet's image-delivering tool. Prefer Niblet MCP for reference inspection and materials. Do not call both providers for the same question or infer connectivity from installation. Consult niblet-catalogue for deployment differences, bounds and licensing.

Use one product-grounded design contract. Niblet's surface modes (Persuade, Operate, Read, Experience) describe the user's job; designer-skill's execution modes (audit, plan, refine, implement, system) describe permitted work. They are independent: an Operate surface can receive a read-only audit or an authorized refinement. Existing product tokens, components and real content win over reference aesthetics. Component retrieval does not authorize dependency installation or source writes, and neither MCP certifies rendered quality.

Example: *"Use designer-skill to redesign this pricing page without breaking functionality."* → get_preflight_brief → dispatch_intent → get_reference → edit → review_and_gate.

Built with it: pythinker.com

References

Plus 26 ux/* references, authored in skills/ux-designer/ and vendored at skills/designer-skill/reference/ux/ (generated by node scripts/sync-ux.mjs, checked by test), so a designer-skill-only install is self-contained. Each SKILL.md is a short router with a one-line description; references load only when a task needs them.

| "make it pop" | `ampl