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To build powerful frontend claude.ai artifacts, follow these steps:
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | web-artifacts-builder |
| description | To build powerful frontend claude.ai artifacts, follow these steps: |
| risk | unknown |
| source | community |
| date_added | 2026-02-27 |
To build powerful frontend claude.ai artifacts, follow these steps:
scripts/init-artifact.shscripts/bundle-artifact.shStack: React 18 + TypeScript + Vite + Parcel (bundling) + Tailwind CSS + shadcn/ui
VERY IMPORTANT: To avoid what is often referred to as "AI slop", avoid using excessive centered layouts, purple gradients, uniform rounded corners, and Inter font.
Run the initialization script to create a new React project:
bash scripts/init-artifact.sh <project-name>
cd <project-name>
This creates a fully configured project with:
@/) configuredTo build the artifact, edit the generated files. See Common Development Tasks below for guidance.
To bundle the React app into a single HTML artifact:
bash scripts/bundle-artifact.sh
This creates bundle.html - a self-contained artifact with all JavaScript, CSS, and dependencies inlined. This file can be directly shared in Claude conversations as an artifact.
Requirements: Your project must have an index.html in the root directory.
What the script does:
.parcelrc config with path alias supportFinally, share the bundled HTML file in conversation with the user so they can view it as an artifact.
Note: This is a completely optional step. Only perform if necessary or requested.
To test/visualize the artifact, use available tools (including other Skills or built-in tools like Playwright or Puppeteer). In general, avoid testing the artifact upfront as it adds latency between the request and when the finished artifact can be seen. Test later, after presenting the artifact, if requested or if issues arise.
This skill is applicable to execute the workflow or actions described in the overview.
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
Helps an AI assistant work with the Miraheze wiki farm — writing wiki requests that get approved, navigating ManageWiki, doing common how-to tasks (templates, skins, permissions, custom domains, backups), writing regex for MediaWiki search-and-replace, AND writing actual article and page content for Miraheze-hosted wikis. Miraheze does NOT ban generative AI; AI-written content is permitted (subject to per-wiki rules). MADE BY SQERSTERS
Helps an AI assistant write, structure, and edit articles in the encyclopedic style of Wikipedia — neutral tone, lead section, summary style, inline citations, no peacock/weasel/persuasive language, and the stub→FA quality ladder. Also covers Simple English Wikipedia rules. MADE BY SQERSTERS