ai-assist-design-creator
Reverse-engineer a website's visual design system from a URL and produce a fully spec-compliant DESIGN.md file (https://github.com/google-labs-code/design.md). The output includes both machine-readable YAML design tokens (colors, typography, spacing, rounded corners, components)
Profil aset
Riset dan pekerjaan pengetahuan
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Skenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Kecocokan Agent
Claude Code + CLI + Codex
Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.
Pasang
Siap
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Pemeliharaan
Terkini
1 hari sejak push
Risiko
Perlu ditinjau
Lisensi tidak jelas
Kualitas GitHub
88
61/100 Kualitas · 59/100 Kepercayaan
Tag cakupan
Catatan ulasan
Lisensi tidak jelas · Dependency or permission surface needs review
Kartu adopsi Agent
Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat
Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.
Kualitas
MenjanjikanUseful candidate, but compare it with alternatives before adopting.
Kepercayaan
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Perlu ditinjauTinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Trust Score OpenAgentSkill v5
Hanya sandbox
Choose a stronger alternative or inspect the source manually before any install attempt.
Star
88 star GitHub
Aktivitas repositori
88 star dan 12 fork
Pemeliharaan
1 hari sejak push
Lisensi
Tidak diketahui
Pasang
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Keamanan pemasangan
Jalur pemasangan paket atau runtime standar
Cakupan izin
secrets or environment access, shell or command execution
Hasil Agent
Belum ada data hasil Agent
Dokumentasi
Konteks README/SKILL.md kuat
Ringkasan risiko
Tinjau sebelum produksi
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- Lisensi tidak jelas
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
Kesiapan pemasangan
Jalur pemasangan tersedia
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Lisensi tidak jelas
- Belum ada bukti hasil Agent-Proven
Metadata yang dapat dibaca Agent
Data keputusan yang dapat dibaca mesin untuk skill ini.
Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.
Tugas yang sesuai
- alur kerja RAG and knowledge
- Tim Claude Code
- builders willing to evaluate younger projects
- Chunk documents
Agent yang sesuai
Keputusan pemasangan
- Perintah
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
- Kebijakan
- Blokir
- Tinjauan manusia
- Ya
Kepercayaan dan risiko
- Kepercayaan
- 51/100
- Audit
- 69/100
- Tingkat risiko
- Perlu ditinjau
Lingkar hasil
- Endpoint
- /api/agent/outcome
- ID event
- resolve
- Hasil
- 5
Perintah pemasangan
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creatorJangan gunakan ketika
- Tim yang membutuhkan SLA dengan dukungan vendor
- production agents without a repository review
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- Petunjuk izin berisiko tinggi: Shell or command execution, Secrets or environment access
- Lisensi tidak jelas
Skill alternatif
Last30days Skill
53.5K Star
npx skills add mvanhorn/last30days-skill -g
Skill alternatif
Academic Research Skills
38.4K Star
npx skills add Imbad0202/academic-research-skills
Skill alternatif
GPT Researcher
28.0K Star
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Star
npx skills add Alibaba-NLP/DeepResearch
Keamanan Agent v2
25/100 · Hindari pemasangan otomatis
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
Tinggi
Eksekusi shell atau perintah
Metadata skill merujuk terminal, CLI, shell, subprocess, atau alur kerja eksekusi perintah.
Sedang
Akses jaringan
Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.
Sedang
Akses sistem file
Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.
Tinggi
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Petunjuk izin berisiko tinggi: Shell or command execution, Secrets or environment access
- Lisensi tidak jelas
Target pemasangan
Pasang skill ini di alur Agent Anda
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-design-creatorRencana resolusi Agent
Biarkan Agent memverifikasi kecocokan sebelum memasang.
API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.
Buka JSON
/api/agent/resolve?task=Use%20ai-assist-design-creator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20ai-assist-design-creator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/jparkerweb-ai-assist-design-creator/install
Agent harus memeriksa
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Salin prompt
Task: Use ai-assist-design-creator in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-design-creator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-design-creator/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Serah-terima Agent
Berikan jalur pemasangan kepada Agent, bukan direktori lain.
Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.
Serah-terima pemasangan
/api/skills/jparkerweb-ai-assist-design-creator/install
Format teks LLM
/api/skills/jparkerweb-ai-assist-design-creator/install?format=text
Cari alternatif
/api/skills/search?q=ai-assist-design-creator&limit=3
Prompt Agent
Use ai-assist-design-creator for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-design-creator/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creatorMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-design-creator
Teks LLM
/api/registry/manifest/jparkerweb-ai-assist-design-creator?format=text
Alias pemasangan
/api/registry/install/jparkerweb-ai-assist-design-creator
Rekomendasikan
/api/registry/recommend?task=Use%20ai-assist-design-creator%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
RAG and knowledge
Tag use case
Platform
Claude Code
Laporan audit
Perlu ditinjau · 69/100
Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Panel keputusan Agent
Fallback candidate for RAG and knowledge
Prototype with this skill first; keep a fallback candidate ready.
Peran di stack
Kandidat cadangan
Kecocokan utama
RAG and knowledge
Label kepercayaan
Buat prototipe dulu
Jalur pemasangan
Perintah siap
Gunakan saat
- alur kerja RAG and knowledge
- Tim Claude Code
- builders willing to evaluate younger projects
Bukti
- recent repository activity
- install command or GitHub repo available
- profil kualitas 61/100
- 3 event interaksi OpenAgentSkill
tinjau dulu
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
Jalur implementasi
- 1Pasang di Agent sandbox dan jalankan satu tugas RAG and knowledge dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil kepercayaan
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adopsi GitHub
Periksa88 star GitHub
Aktivitas star/fork
Periksa88 star dan 12 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus1 hari sejak push
Kejelasan lisensi
PeriksaTidak diketahui
Sinyal positif
- Tinjauan AI disetujui
- Jalur pemasangan tersedia
- Bukti repositori tersedia
- Repositori yang baru dipelihara
- Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
- Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama
Tinjau sebelum memasang
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- Lisensi tidak jelas
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Belum ada laporan hasil Agent nyata
- Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan
Tindakan yang disarankan
Choose a stronger alternative or inspect the source manually before any install attempt.
Profil kualitas
Menjanjikan kandidat untuk alur kerja Agent
Useful candidate, but compare it with alternatives before adopting.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Daftar alternatif
Bandingkan sebelum memasang
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Ringkasan
--- name: ai-assist-design-creator description: "Reverse-engineer a website's visual design system from a URL and produce a fully spec-compliant DESIGN.md file (https://github.com/google-labs-code/design.md). The output includes both machine-readable YAML design tokens (colors, typography, spacing, rounded corners, components) and human-readable markdown rationale sections (Overview, Colors, Typography, Layout, Elevation & Depth, Shapes, Components, Do's and Don'ts). Use this skill whenever the user wants to generate a DESIGN.md, create a design system file from a website, capture a site's visual identity, extract design tokens, build a design spec from a URL, clone a site's look and feel, or scaffold a DESIGN.md from scratch. Also triggers on: 'design system from URL', 'generate DESIGN.md', 'extract colors from site', 'what are this site's design tokens', 'capture design from website'." argument-hint: "[URL of the site to reverse-engineer, or leave blank to be prompted]" ---
# DESIGN.md Creator
Reverse-engineer a website's visual design system and produce a fully spec-compliant `DESIGN.md` file following the [google-labs-code/design.md](https://github.com/google-labs-code/design.md) format.
## What this produces
A `DESIGN.md` file with two layers: 1. **YAML frontmatter** — machine-readable design tokens: colors, typography, spacing, rounded corners, components 2. **Markdown body** — human-readable rationale for each design decision, in 8 canonical sections
The output is ready for agents to consume immediately — no post-processing needed.
## Step 1: Get the URL
If the user provided a URL via `$ARGUMENTS`, use it. Otherwise ask:
> What website should I reverse-engineer? Provide the URL and I'll generate a DESIGN.md from its visual design. > > Optionally, also tell me: > - Where to save the file (default: `DESIGN.md` in the current directory) > - Whether this is a dark-mode or light-mode site (I'll detect this automatically if you don't know) > - Any specific components you want captured (buttons, cards, inputs, nav, etc.)
Wait for the URL before proceeding.
## Step 2: Fetch and analyze the site
Fetch the page and all significant visual signals:
1. **Fetch the main URL** — use whichever method your agent environment supports: - **`curl`** (works in any agent with shell access): `curl -sL --max-time 15 -A "Mozilla/5.0" "<URL>"` — captures raw HTML including `<style>` blocks and inline CSS - **`webfetch` tool** (if your agent provides it natively): use it directly for cleaner content extraction - If the initial fetch returns no CSS (JS-heavy SPA), also fetch the page's linked `.css` files: extract `<link rel="stylesheet" href="...">` URLs from the HTML, resolve each href to an absolute URL using the page's final URL after redirects (e.g., `/assets/app.css` → `https://example.com/assets/app.css`, `//cdn.example.com/app.css` → `https://cdn.example.com/app.css`), de-duplicate, then `curl` each one 2. **Identify key sub-pages** — if the site has a component library, style guide, or "About" page, fetch those too (up to 2–3 additional pages) to improve coverage 3. **Look for existing design system artifacts** — check for `/design-tokens.json`, `/tokens.json`, `tailwind.config.js`, or any design system links in the page source
What to extract from the fetched content:
| Signal | Where to look | |--------|--------------| | Brand colors | CSS variables (`--color-*`, `--primary`, etc.), inline styles, og:image colors, logo | | Typography | `font-family`, `font-size`, `font-weight`, `line-height`, `letter-spacing` in CSS | | Spacing scale | `--spacing-*`, padding/margin patterns, grid gutter values | | Corner radii | `border-radius` values across buttons, cards, inputs | | Elevation | `box-shadow`, `backdrop-filter`, `z-index` layering patterns | | Component styles | Button, card, input, nav, badge styles from class names or CSS | | Design personality | Logo, imagery, copy tone, overall layout density |
> **Note:** You're inferring from observed CSS/HTML. Be honest about what you can directly observe vs. what you're inferring from visual patterns. Dark-mode sites typically have low-luminance surface colors and high-contrast text; light-mode sites are the inverse. When you can't determine an exact hex value, make a design-coherent choice and note it in the prose.
## Step 3: Build the DESIGN.md
Read `references/design-md-spec.md` for the complete token schema and section rules.
### Token extraction rules
**Colors** — Extract the site's full color role set. At minimum: - `primary` — main brand/action color - `secondary` — supporting accent or secondary brand color - `neutral` / `surface` — background/surface color - `on-primary`, `on-surface` — text colors on those surfaces - Include semantic colors if detectable: `error`, `warning`, `success` - Name tokens semantically (`primary`, `secondary`, `tertiary`, `neutral`) or use Material Design role names if the site uses a Material-style palette
**Typography** — Identify the main type scale. Typically 5–12 levels: - Display/headline levels (large, impactful headings) - Body levels (body-lg, body-md, body-sm) - Label levels (captions, tags, small UI text) - Include all detectable properties: `fontFamily`, `fontSize`, `fontWeight`, `lineHeight`, `letterSpacing` - Dimensions must include units: `px`, `em`, or `rem`
**Spacing** — Extract the spacing scale. Common pattern: a base unit (4px or 8px) with named steps: `xs`, `sm`, `md`, `lg`, `xl`. Also include layout-specific values like `gutter`, `margin`, `container-max`.
**Rounded** — Extract corner radius values. Name them: `sm`, `DEFAULT`, `md`, `lg`, `xl`, `full` (for pill shapes).
**Components** — Capture 4–8 key components. For each, include as many valid properties as observed: `backgroundColor`, `textColor`, `typography` (token ref), `rounded` (token ref), `padding`, `height`, `width`. Use token references like `{colors.primary}` instead of hardcoded hex values wherever possible. Include hover variants as separate entries (e.g., `button-primary-hover`).
### Sections to write
Write all 8 sections in canonical order. Each section combines YAML tokens (defined in frontmatter) with prose rationale. For sections where tokens aren't applicable (Elevation, Shapes, Do's and Don'ts), write prose only.
1. **Overview** — Brand personality, target audience, emotional tone, design style (flat, glassmorphism, neumorphism, material, etc.), key design decisions. 2–4 sentences that give a coherent aesthetic picture.
2. **Colors** — Describe the role of each color palette entry. What does each color *mean* in the design? When is it used? Reference the token names.
3. **Typography** — Describe the font strategy: which typefaces, why they were chosen, how the scale is organized, any special treatments (tight tracking on headlines, text-shadow on dark backgrounds, etc.).
4. **Layout** — Grid system (fluid, fixed, 12-column?), spacing philosophy (8px grid, dense vs. airy), max-width, container strategy.
5. **Elevation & Depth** — How visual hierarchy is communicated: shadows, tonal layers, glassmorphism, borders, z-axis layering. If flat design, describe what replaces shadows.
6. **Shapes** — Corner radius philosophy: sharp/technical, soft/organic, fully rounded pills, mixed. Which components use which radius.
7. **Components** — Walk through the key component tokens and explain the design rationale for each group (action elements, containers, inputs, typography application).
8. **Do's and Don'ts** — 3–5 concrete rules for maintaining design consistency. Things like "always use `{colors.primary}` for CTAs, never `{colors.secondary}`" or "never use pure black (#000000) for text — use `on-surface`".
### YAML frontmatter structure
```yaml --- name: <Site/Brand Name> description: <optional one-line brand tagline> colors: primary: "#XXXXXX" ... typography: headline-lg: fontFamily: <font> fontSize: <Npx> fontWeight: <number> lineHeight: <1.2 or 24px> letterSpacing: <-0.02em or 1px> ... rounded: sm: <Npx or Nrem> ... spacing: base: <Npx> ... components: button-primary: backgroundColor: "{colors.primary}" ... ... --- ```
## Step 4: Validate and save
After generating the content:
1. **Self-check** these things before writing the file: - All token references (`{path.to.token}`) resolve to a defined token - Color values start with `#` followed by 6 hex digits - All dimension values have units (`px`, `em`, `rem`) — no bare numbers except: font weights, unitless line-height multipliers, and `spacing` values (which may be unitless ratios or column counts per the spec) - Section order matches the canonical order (Overview → Colors → Typography → Layout → Elevation & Depth → Shapes → Components → Do's and Don'ts) - Component properties: canonical keys (`backgroundColor`, `textColor`, `typography`, `rounded`, `padding`, `size`, `height`, `width`) pass the linter silently; unknown keys are accepted by the spec but will produce a linter warning — flag them in the confidence notes
2. **Check for an existing file** at the target path before writing: - If `DESIGN.md` (or the user-specified path) already exists, warn the user: "A `DESIGN.md` already exists at this path. Overwrite, save as `DESIGN-<site-name>.md`, or cancel?" Wait for their choice before writing. - If no file exists, proceed directly.
3. **Save the file** as `DESIGN.md` in the current working directory (or the path the user specified).
4. **Tell the user** what was generated:
> `DESIGN.md` saved. > > **Design system:** [Name] > **Style:** [e.g., Glassmorphism / Flat / Material / Custom] > **Colors:** [N tokens] — [brief palette description] > **Typography:** [N levels] — [font family names] > **Components:** [list of captured components] > > **Confidence notes:** > - [Any values that were inferred rather than directly observed] > - [Any sections that had limited CSS data and required design judgment] > > Want me to refine any section, add more components, or lint the file with `npx @google/design.md lint DESIGN.md`?
## Recovery
| Situation | How to handle | |-----------|--------------| | `webfetch` not available | Fall back to `curl -sL --max-time 15 -A "Mozilla/5.0" "<URL>"` — available in any agent with shell access | | Site blocks fetch (403/429) | Ask user to paste relevant CSS, screenshot, or describe the design manually | | JS-heavy SPA with no inline CSS | Fetch the JS bundle URL if visible; also try fetching linked `.css` files directly; ask user for computed styles or a screenshot as a last resort | | Can't determine exact hex values | Make design-coherent color choices; note them as "inferred" in prose and confidence notes | | Site uses a known design system (Material, Ant, Chakra, Tailwind UI) | Note this in the Overview — tokens will align with that system's defaults | | No typography found | Default to system fonts (Inter, -apple-system) and note it | | User wants lint | Run `npx @google/design.md lint DESIGN.md` and surface any errors/warnings |
## Rules
- Never fabricate specific brand hex values with false certainty — if you inferred a color, say so - All token cross-references must point to defined tokens — no dangling refs - Dimensions must always have units (exception: unitless `lineHeight` multipliers like `1.5` are valid) - The YAML frontmatter is normative; prose is explanatory context — don't contradict one with the other - Output goes in the current working directory as `DESIGN.md` unless the user specifies otherwise - If a section has genuinely no applicable content (e.g., a flat design with no elevation), include it briefly and explain: "This design system uses flat tonal layering rather than shadows — see Colors for the tonal surface stack"
Detail teknis
- Versi
- 1.0.0
- Lisensi
- Unknown
- Pembaruan terakhir
- 23 Agu 2026
- Diterbitkan
- 21 Agu 2026
Ringkasan keputusan
Kandidat cadangan
recent repository activity
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 62/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- Tingkat sukses
- —
- Kegagalan terbaru
- —
- Hasil
- 0
- Kualitas output
- —
- Gagal
- 0
- Tidak relevan
- 0
- Pemasangan
- 0
- Diblokir risiko
- 0
- Perlu penyiapan
- 0
- Produksi
- 0
Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.
Pasang
Tambahkan ke alur Agent
Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.
Siklus pertumbuhan
Kit berbagi
Draf berbasis skenario untuk ai-assist-design-creator, siap untuk posting manual di X.
ai-assist-design-creator: Reverse-engineer a website's visual design system from a URL and produce a fully spec-complia... 88 stars https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator?ref=x
Balasan opsional dengan perintah pemasangan
Listing + install path for ai-assist-design-creator: https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator?ref=x Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Sumber listing
Diindeks Registry
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- jparkerweb
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
Klaim skill iniKlaim pemilik
Klaim listing skill ini
Listing Diindeks Registry ini dikaitkan dengan jparkerweb, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.
Kit backlink kreator
Tambahkan badge bukti ke README Anda
Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-design-creator)Penulis
jparkerweb
@jparkerweb
Tag
Kecocokan platform
Sinyal kesehatan
- Star GitHub
- 88
- Skor kualitas
- 37/100
- Push GitHub terakhir
- 22 Agu 2026
- Petunjuk framework
- Tidak diketahui
- Tampilan OpenAgentSkill
- 3
- Salinan pemasangan
- 0
- Klik keluar
- 0
Sinyal komunitas
Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.
Kepercayaan & keamanan
Do not auto-install
- Adopsi GitHub88 star GitHubPeriksa
- Aktivitas star/fork88 star dan 12 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
- Pemeliharaan terbaru1 hari sejak pushLulus
- Kejelasan lisensiTidak diketahuiPeriksa
- Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
- Risiko dependensi/runtimecommand execution surface, credential or environment accessPerbaiki
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