Omh Design Quality Gate logo

Omh Design Quality Gate

CommunityPopular
rlaope
omh-design-quality-gate

[omh] Hermes Design Quality Gate workflow: enforce superior content, design, layout, publishing, and visual QA gates. Use when the user says: design-quality-gate, design quality gate, ui ux pro max, design pro max, frontend pro max, visual qa pro, premium design, high quality design.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-design-quality-gate
Stars
2.7K
Forks
194
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by rlaope on GitHub. Read the source before you install it.

Installation

Install the Omh Design Quality Gate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-design-quality-gate .claude/skills/omh-design-quality-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Design Quality Gate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Omh Design Quality Gate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Omh Design Quality Gate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Design Quality Gate

This is an OMH design-quality-gate workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

design-quality-gate makes high-stakes visual deliverables premium and trustworthy by treating taste, content, layout, accessibility, and render QA as first-class evidence.

Do Not Use When

  • Basic image prompt card only; use img-summary.
  • The artifact is a throwaway probe whose quality is irrelevant to the decision it answers; use decision-prototype.
  • Ordinary file packaging/export plan only; use materials-package or deliverable-package.
  • Pure backend, CLI, data, or text-only research with no visual surface.
  • The user asks to claim deployment, export, publication, or visual QA without evidence.

Examples

Good example:

  • Prompt: design-quality-gate make this landing page and deck premium and verified.
  • Expected behavior: Prepare design_quality_gate/v1 with references, comparative_quality_rubric/v1, surface_quality_matrix/v1, hierarchy, layout plan, visual QA checklist, route, and evidence boundaries.
  • Why: The request asks for superior visual quality and publishing readiness.

Bad example:

  • Prompt: design-quality-gate say the PDF and website look amazing because the plan says so.
  • Expected behavior: Require rendered PDF/page screenshots or mark visual QA as not_observed.
  • Why: A quality brief is not render, visual QA, export, deployment, or delivery evidence.

Completion Checklist

  • The surface, audience, source content, baseline/reference bar, and artifact type are named.
  • The comparative_quality_rubric/v1 explains how the result must beat ordinary output.
  • The surface_quality_matrix/v1 covers web, deck/PPT, PDF/poster, accessibility, and CJK-relevant checks as applicable.
  • Prepared quality gates, generated artifacts, visual QA, export, publication, approval, and delivery remain separate states.
  • The next action names whether to revise content, prepare implementation/export handoff, gather render evidence, or report blocked QA.

Recovery Notes

  • If the baseline or references are missing, prepare the gate with an explicit comparative-quality gap instead of calling the result premium.
  • If render QA is unavailable, keep PASS unavailable and ask for the smallest screenshot, deck/PDF render, or operator observation that proves the target surface.

Use When

Use when web UI, decks, PDFs, posters, or visual packages must beat ordinary output on content, taste, layout, accessibility, and render QA.

Strong routing signals: `design-quality-gate`, `design quality gate`, `ui ux pro max`, `design pro max`, `frontend pro max`, `visual qa pro`, `premium design`, `high quality design`, `beautiful website`, `frontend publishing`, `publishing quality`, `layout validation`, `ppt design quality`, `pdf design quality`, `デザイン品質ゲート`, `公開品質のデザイン`, `デザインの品質基準`, `웹사이트 디자인`, `프론트엔드 퍼블리싱`, `레이아웃 검증`, `더 뛰어나게`, `고퀄`, `设计质量门禁`, `发布级设计`, `设计质量标准`

Catalog Metadata

Category: materials Phase: design-quality-gate Quality tier: design-pro-gated Reasoning demand: standard

Quality bar:

  • Define superior design quality with references, audience, hierarchy, style, and measurable QA gates. The bar is named, not relative: what a senior product designer at a top-tier product company (the Linear/Stripe/Supabase class) would sign off on — technically clean but flat output fails it. Load references/design-critique-rubric.md and judge every axis with named evidence.
  • State why the result should be better than ordinary output, including content depth, visual hierarchy, spacing, typography, and interaction or export polish.
  • Review content accuracy and hierarchy before visual polish.
  • Use design-system/reference rules for web, deck, PDF, and poster surfaces.
  • Reject generic AI slop: weak hierarchy, cramped copy, flat templates, one-note palettes, and unverified exports.
  • Require fresh visual QA for pages, slides, states, viewports, and CJK-heavy regions before PASS.

Required inputs:

  • surface/channel
  • audience and purpose
  • source content or gaps
  • style references
  • ordinary-output baseline or competitor/reference quality bar
  • viewport/page/export constraints
  • observed render QA for completion claims

Expected outputs:

  • design_quality_gate/v1
  • content_quality_review/v1
  • surface_quality_matrix/v1
  • comparative_quality_rubric/v1
  • layout_validation_plan/v1
  • visual_qa_evidence/v1 when observed
  • publishing_readiness/v1
  • downstream route: frontend, materials-package, img-summary, or deliverable-package

Artifact expectations:

  • design_quality_gate/v1 when prepared
  • surface_quality_matrix/v1 with web: responsive viewport, deck/PPT: slide rhythm, PDF/poster: print-safe, and accessibility/CJK checks
  • comparative_quality_rubric/v1 that names how this should be better than ordinary output
  • visual_qa_evidence/v1 only from fresh screenshots/renders/observations
  • export/publish evidence only when observed

Safety rules:

  • Require references/rubric plus fresh render QA before PASS.
  • Never claim PPTX, PDF, deployment, poster export, image generation, or publication without observed evidence.
  • Separate content, taste, layout, accessibility, render fidelity, and delivery checks.
  • Route web to frontend, binary files to materials/deliverable package, and image cards to img-summary.
  • For Korean/CJK text, awkward breaks, clipped glyphs, orphan particles, or tiny copy block visual QA.
  • Do not call a result high-quality unless it is compared against a named ordinary-output baseline or references.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Report actual tool results or not_observed / not_available; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Omh Design Quality Gate AI skill do?

[omh] Hermes Design Quality Gate workflow: enforce superior content, design, layout, publishing, and visual QA gates. Use when the user says: design-quality-gate, design quality gate, ui ux pro max, design pro max, frontend pro max, visual qa pro, premium design, high quality design.

Why use Omh Design Quality Gate on TypingMind?

Because you install it once and use it with any model. Omh Design Quality Gate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Omh Design Quality Gate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-design-quality-gate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Omh Design Quality Gate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Omh Design Quality Gate?

As many as you like. As long as a model supports skills, you can use Omh Design Quality Gate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Omh Design Quality Gate AI skill free?

Yes. It is published on GitHub by rlaope under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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