Artifact Testing

Community

win4r

artifact_testing

Verify an artifact before delivering it - file deliverables (pdf, pptx, docx, xlsx, csv) and web artifacts alike. Use whenever a build is about to return a link, or a build task asks for validation, QA, or a visual check. Covers the per-kind gate scripts, render-and-look verification, and leftover-placeholder scanning.

Overview

Publisher	win4r
Repository	`MuseAI-Skills`
Skill name	`artifact_testing`
Stars	382
Forks	116
Bundled files	Instructions only
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by win4r on GitHub. Read the source before you install it.

Installation

Install the Artifact Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/artifacts/testing
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.

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/win4r/MuseAI-Skills.git /tmp/MuseAI-Skills
mkdir -p .claude/skills
cp -r /tmp/MuseAI-Skills/opt/hatch/skills/artifacts/testing .claude/skills/artifact_testing

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Artifact Testing 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 Artifact Testing 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 Artifact Testing 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.

Artifact verification

One home for verification across the artifact namespace. The rule every kind shares: a deliverable is verified by looking at what the user will see, freshly rendered, not by trusting the code that produced it. Never return a link while a gate below fails; after three failed fix attempts, report the specific failure and ask for direction instead of iterating.

File kinds: gates, then eyes

Kind	Gate
pdf	`render_audit.mjs` with the flags the pdf skill's `workflow.md` names, then `/opt/hatch/skills/artifacts/scripts/validate_pdf.sh`
presentation	`assemble_deck.mjs`, then `render_audit.mjs` with the flags `workflow.md` names
docx	render to PDF with headless LibreOffice (`soffice --headless --convert-to pdf`), then rasterize (`pdftoppm -jpeg -r 100`)
xlsx	`/opt/hatch/skills/artifacts/scripts/validate_xlsx.py`
csv / md	parse it back (csv: a Python `csv` read; md: read the file)

The shared render engine is /opt/hatch/skills/artifacts/scripts/render_audit.mjs; renders outlast muse.exec's default yield, so size yield_ms past the expected runtime and read the report file the flags name rather than trusting a backgrounded command's silence.

Then look. Read every validation PNG or page image with fresh eyes - the generating context sees what it expects, not what rendered. Check first for text overflow or cut-off content, then overlaps, collisions, cramped or uneven spacing, low-contrast text, and template decoration left behind.

Placeholder scan. Before returning, search the deliverable's text for leftover scaffolding: TODO, lorem, placeholder, [insert, xxx runs, and sample rows the user never asked for. Anything found is fixed, not shipped.

Web artifacts

Web builds keep their own audit tools (web_artifacts.build and web_artifacts.audit run the same capture engine with enforcement); this skill's render-fresh and placeholder rules apply to their output all the same.

Frequently asked questions

What does the Artifact Testing AI skill do?

Why use Artifact Testing on TypingMind?

Because you install it once and use it with any model. Artifact Testing 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 Artifact Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/artifacts/testing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Artifact Testing?

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 Artifact Testing?

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

Is the Artifact Testing AI skill free?

It is published on GitHub by win4r. Check the repository for licensing terms. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Artifact verification

File kinds: gates, then eyes

Web artifacts

Frequently asked questions

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