Creador · jparkerweb
Última actualización · 23 ago 2026
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)
Do not auto-install
Destinos de instalación
Prompt de instalación para Codex
Install the "ai-assist-design-creator" agent skill from https://github.com/jparkerweb/ai-assist-skills/tree/main/skills/ai-assist-design-creator. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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'. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"jparkerweb-ai-assist-design-creator","task":"Install ai-assist-design-creator","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Perfil del activo
Investigación y trabajo de conocimiento
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Escenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Afinidad con Agent
Claude Code + CLI + Codex
Funciona con Codex, Claude Code, Cursor, CLI o Agents personalizados.
Instalar
Listo
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Mantenimiento
Actual
2 días desde el último push
Riesgo
Requiere revisión
La licencia no está clara
Calidad de GitHub
88
61/100 Calidad · 59/100 Confianza
Etiquetas de cobertura
Notas de revisión
La licencia no está clara · Dependency or permission surface needs review
Tarjeta de adopción del Agent
Confianza, auditoría y preparación de instalación de un vistazo
Estas puntuaciones combinan metadatos públicos del repositorio, señales de revisión de OpenAgentSkill, actualidad de mantenimiento y preparación de instalación. Sirven para preseleccionar; no sustituyen la revisión humana.
Calidad
PrometedorUseful candidate, but compare it with alternatives before adopting.
Confianza
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Auditoría
Requiere revisiónRevisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Trust Score de OpenAgentSkill v5
Solo sandbox
Choose a stronger alternative or inspect the source manually before any install attempt.
Estrellas
88 estrellas de GitHub
Actividad del repositorio
88 estrellas y 12 forks
Mantenimiento
2 días desde el último push
Licencia
Desconocido
Instalar
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
Seguridad de instalación
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
secrets or environment access, shell or command execution
Resultados del Agent
Aún no hay datos de resultados del Agent
Documentación
Contexto sólido de README/SKILL.md
Resumen de riesgo
Revisar antes de producción
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- La licencia no está clara
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
Preparación de instalación
Ruta de instalación disponible
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- La licencia no está clara
- Aún no hay evidencia de resultados Agent-Proven
Metadatos legibles por Agent
Datos de decisión legibles por máquina para este skill.
Usa este bloque o el JSON integrado para decidir si un Agent debe instalar este skill, elegir una alternativa o pedir revisión humana primero.
View technical data+
Metadatos legibles por Agent
Datos de decisión legibles por máquina para este skill.
Usa este bloque o el JSON integrado para decidir si un Agent debe instalar este skill, elegir una alternativa o pedir revisión humana primero.
Tareas adecuadas
- flujos de RAG and knowledge
- Equipos de Claude Code
- builders willing to evaluate younger projects
- Chunk documents
Agents adecuados
Decisión de instalación
- Comando
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creator
- Política
- Bloquear
- Revisión humana
- Sí
Confianza y riesgo
- Confianza
- 51/100
- Auditoría
- 69/100
- Nivel de riesgo
- Requiere revisión
Ciclo de resultados
- Endpoint
- /api/agent/outcome
- ID del evento
- resolve
- Resultados
- 5
Comando de instalación
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-design-creatorNo usar cuando
- Equipos que necesitan un SLA con soporte del proveedor
- production agents without a repository review
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- La licencia no está clara
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Seguridad de Agent v2
25/100 · Evitar instalación automática
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.
Alto
Ejecución de shell o comandos
Los metadatos del skill hacen referencia a terminal, CLI, shell, subprocesos o flujos de ejecución de comandos.
Medio
Acceso a red
El skill probablemente consulta páginas remotas, API, repositorios o servicios externos.
Medio
Acceso al sistema de archivos
El skill puede leer o escribir archivos de proyecto, documentos, artefactos generados o estado local.
Alto
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- La licencia no está clara
Plan de resolución de Agent
Deja que un Agent valide el ajuste antes de instalar.
La API Resolve devuelve la skill elegida, alternativas, política de seguridad, notas de auditoría, destino de instalación y un prompt listo para usar.
Abrir JSON
/api/agent/resolve?task=Use%20ai-assist-design-creator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texto de Resolve
/api/agent/resolve?task=Use%20ai-assist-design-creator%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Traspaso de instalación
/api/skills/jparkerweb-ai-assist-design-creator/install
Agent debe revisar
- 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.
Copiar 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.Traspaso de Agent
Da al Agent la ruta de instalación, no otro directorio.
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
Traspaso de instalación
/api/skills/jparkerweb-ai-assist-design-creator/install
Formato de texto LLM
/api/skills/jparkerweb-ai-assist-design-creator/install?format=text
Buscar alternativas
/api/skills/search?q=ai-assist-design-creator&limit=3
Prompt de 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-creatorMetadatos del Registry
Perfil legible por Agent para seleccionar skills automáticamente.
La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-design-creator
Texto LLM
/api/registry/manifest/jparkerweb-ai-assist-design-creator?format=text
Alias de instalación
/api/registry/install/jparkerweb-ai-assist-design-creator
Recomendar
/api/registry/recommend?task=Use%20ai-assist-design-creator%20in%20an%20agent%20workflow&limit=3
Afinidad con Agent
RAG and knowledge
Etiquetas de uso
Plataformas
Claude Code
Informe de auditoría
Requiere revisión · 69/100
Revisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Panel de decisión de Agent
Fallback candidate for RAG and knowledge
Prototype with this skill first; keep a fallback candidate ready.
Rol en la pila
Candidata de respaldo
Ajuste principal
RAG and knowledge
Etiqueta de confianza
Prototipar primero
Ruta de instalación
Comando listo
Úsalo cuando
- flujos de RAG and knowledge
- Equipos de Claude Code
- builders willing to evaluate younger projects
Evidencia
- recent repository activity
- install command or GitHub repo available
- perfil de calidad 61/100
- 3 eventos de interacción de OpenAgentSkill
revisar primero
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
Ruta de implementación
- 1Instálalo en un Agent de sandbox y ejecuta una tarea de RAG and knowledge de principio a fin.
- 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.
Perfil de confianza
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adopción en GitHub
Revisar88 estrellas de GitHub
Actividad de stars/forks
Revisar88 estrellas y 12 forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado2 días desde el último push
Claridad de licencia
RevisarDesconocido
Señales positivas
- Revisión de IA aprobada
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- Repositorio mantenido recientemente
- El comando de instalación no muestra un patrón de alto riesgo evidente
- El ciclo de resultados está listo, pero necesita la primera ejecución real de Agent
Revisar antes de instalar
- Repository license is listed as 'Unknown' by GitHub; consider adding an explicit license to clarify usage rights.
- La licencia no está clara
- 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
- Aún no hay informes reales de resultados del Agent
- Se requiere revisión humana antes de una instalación desatendida
Acción recomendada
Choose a stronger alternative or inspect the source manually before any install attempt.
Perfil de calidad
Prometedor candidato para flujos de Agent
Useful candidate, but compare it with alternatives before adopting.
Ajuste de flujo
Usa esta skill en estos escenarios
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Investigate faster
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Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Ajuste de flujo
Añadir a un flujo completo
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.
Lista de alternativas
Compara antes de instalar
Similar skills that may fit this task.
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Resumen
--- 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"
Detalles técnicos
- Versión
- 1.0.0
- Licencia
- Unknown
- Última actualización
- 23 ago 2026
- Publicado
- 21 ago 2026
Resumen de decisión
Candidata de respaldo
recent repository activity
Auditoría
Revisión de instalación
Revisión de instalación y adopción
- Seguridad
- 62/100
- Mantenimiento
- 100/100
- Instalar
- 92/100
Evidencia probada por Agent
Evidencia probada por Agent
Informes de resultados tras resolver, revisar, instalar y una ejecución limitada.
- Tasa de éxito
- —
- Fallo reciente
- —
- Resultados
- 0
- Calidad de salida
- —
- Fallidos
- 0
- No relevante
- 0
- Instalaciones
- 0
- Bloqueado por riesgo
- 0
- Configuración necesaria
- 0
- Producción
- 0
Aún no hay datos de resultados de Agent. La primera ejecución puede informar éxito, configuración necesaria, bloqueos de riesgo, fallo o irrelevancia mediante /api/agent/outcome.
Instalar
Añadir al flujo de Agent
Gratis y de código abierto. Revisa el informe antes de instalar en Agents de producción.
Bucle de crecimiento
Kit para compartir
Borrador basado en un caso para ai-assist-design-creator, listo para publicar manualmente en 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
Respuesta opcional con comando de instalación
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
Fuente de la ficha
Indexado por Registry
Esta ficha se indexó desde fuentes públicas y no está marcada como oficial hasta que se apruebe una reclamación de mantenedor.
- Creador
- jparkerweb
- Indexado por
- Índice comunitario de OpenAgentSkill
La atribución enlaza al repositorio público o al perfil del creador. Los creadores pueden reclamar la ficha para actualizar las señales de propiedad.
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Esta ficha Indexado por Registry se atribuye a jparkerweb, pero aún no está marcada como oficial. Reclámala para añadir una señal de propietario verificado y hacer más fiables futuras actualizaciones de lanzamiento, instalación y auditoría.
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Muestra la ficha canónica, las señales actuales de confianza y auditoría, y evidencia real de Agent-Proven donde los desarrolladores evalúan el repositorio.
[](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)Autor
jparkerweb
@jparkerweb
Etiquetas
Afinidad con plataforma
Señales de salud
- Estrellas de GitHub
- 88
- Puntuación de calidad
- 37/100
- Último push de GitHub
- 22 ago 2026
- Pistas del framework
- Desconocido
- Vistas de OpenAgentSkill
- 3
- Copias de instalación
- 0
- Clics externos
- 0
Señal de comunidad
Comparte si este skill resulta útil para tu flujo de Agent. Los comentarios agregados mejoran la clasificación con el tiempo.
Confianza y seguridad
Do not auto-install
- Adopción en GitHub88 estrellas de GitHubRevisar
- Actividad de stars/forks88 estrellas y 12 forks; la actividad de issues no está disponible en los metadatos actualesRevisar
- Mantenimiento reciente2 días desde el último pushAprobado
- Claridad de licenciaDesconocidoRevisar
- Completitud de README/SKILL.mdLos metadatos incluyen suficiente contexto de uso y flujo de trabajoAprobado
- Riesgo de dependencias/runtimecommand execution surface, credential or environment accessCorregir
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