ai-assist-prototype
Build self-contained, double-click-to-open HTML prototypes so the user can vet an interface before it gets built. One file holds several structurally different variants of a page, app screen, component, flow, or terminal/TUI layout (rendered in-browser), plus a draggable Design D
Perfil del activo
Diseño y producción creativa
Design assets, images, video, audio, multimodal media, presentation, and creative production skills.
Escenario
Diseño y creatividad
I need my agent to produce design assets, UI directions, presentations, or creative media workflows.
Afinidad con Agent
Claude Code + Cursor + Browser agents
Funciona con Codex, Claude Code, Cursor, CLI o Agents personalizados.
Instalar
Listo
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototype
Mantenimiento
Actual
Actualizado hoy
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
Revisión humana antes de instalar
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
Actualizado hoy
Licencia
Desconocido
Instalar
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototype
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 unknown (GitHub detected 'Unknown'), which creates legal ambiguity for users and contributors.
- Financial research output is not financial advice; require human review before any live investment decision.
- La licencia no está clara
- Quality score needs review
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.
Tareas adecuadas
- flujos de Browser automation
- Equipos de Claude Code
- builders willing to evaluate younger projects
- Navigate pages
Agents adecuados
Decisión de instalación
- Comando
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototype
- 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-prototypeNo usar cuando
- Equipos que necesitan un SLA con soporte del proveedor
- production agents without a repository review
- Repository license is unknown (GitHub detected 'Unknown'), which creates legal ambiguity for users and contributors.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- La licencia no está clara
Skill alternativo
Frontend Design
170.9K Estrellas
npx skills add anthropics/skills --skill frontend-design
Skill alternativo
Taste Skill: Anti-Slop Frontend
79.0K Estrellas
npx skills add Leonxlnx/taste-skill --skill design-taste-frontend
Skill alternativo
Canvas Design
170.9K Estrellas
npx skills add anthropics/skills --skill canvas-design
Skill alternativo
Anthropic Brand Guidelines
170.9K Estrellas
npx skills add anthropics/skills --skill brand-guidelines
Seguridad de Agent v2
21/100 · 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
Browser automation
Skill may drive a browser or interact with web pages.
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.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- La licencia no está clara
Destinos de instalación
Instala este skill en tu flujo de Agent
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
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-prototypePlan 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-prototype%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texto de Resolve
/api/agent/resolve?task=Use%20ai-assist-prototype%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Traspaso de instalación
/api/skills/jparkerweb-ai-assist-prototype/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-prototype in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-prototype%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-prototype/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototype
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-prototype/install
Formato de texto LLM
/api/skills/jparkerweb-ai-assist-prototype/install?format=text
Buscar alternativas
/api/skills/search?q=ai-assist-prototype&limit=3
Prompt de Agent
Use ai-assist-prototype for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-prototype/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototypeMetadatos 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-prototype
Texto LLM
/api/registry/manifest/jparkerweb-ai-assist-prototype?format=text
Alias de instalación
/api/registry/install/jparkerweb-ai-assist-prototype
Recomendar
/api/registry/recommend?task=Use%20ai-assist-prototype%20in%20an%20agent%20workflow&limit=3
Afinidad con Agent
Browser automation
Etiquetas de uso
Plataformas
Claude Code, Cursor, Browser agents
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 Browser automation
Prototype with this skill first; keep a fallback candidate ready.
Rol en la pila
Candidata de respaldo
Ajuste principal
Browser automation
Etiqueta de confianza
Prototipar primero
Ruta de instalación
Comando listo
Úsalo cuando
- flujos de Browser automation
- 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
- 1 eventos de interacción de OpenAgentSkill
revisar primero
- Repository license is unknown (GitHub detected 'Unknown'), which creates legal ambiguity for users and contributors.
Ruta de implementación
- 1Instálalo en un Agent de sandbox y ejecuta una tarea de Browser automation 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
AprobadoActualizado hoy
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 unknown (GitHub detected 'Unknown'), which creates legal ambiguity for users and contributors.
- Financial research output is not financial advice; require human review before any live investment decision.
- 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
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Ajuste de flujo
Añadir a un flujo completo
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
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.
Lista de alternativas
Compara antes de instalar
Similar skills that may fit this task.
Frontend Design
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Taste Skill: Anti-Slop Frontend
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Canvas Design
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
Anthropic Brand Guidelines
Apply Anthropic official brand colors, typography, and visual standards to appropriate Anthropic-related artifacts.
Resumen
--- name: ai-assist-prototype description: "Build self-contained, double-click-to-open HTML prototypes so the user can vet an interface before it gets built. One file holds several structurally different variants of a page, app screen, component, flow, or terminal/TUI layout (rendered in-browser), plus a draggable Design Deck for flipping between variants, tuning fonts, colors, spacing, shape, motion and 'feel' with live dials, trying vibe presets, checking viewport sizes and light/dark, pinning comments on elements, and an 'Export to LLM' button that copies the chosen variant and every dial value as a handoff block to paste back to the agent. Use this whenever the user wants to prototype, mock up, wireframe, explore options for, or sanity-check a UI (landing page, dashboard, settings page, onboarding, form, mobile screen, component, CLI/TUI layout), or says 'what should this look like', 'show me a few options', 'let me tweak it before we build', 'vet the design'. Also use it when the user pastes a block starting with 'AI-ASSIST PROTOTYPE HANDOFF': that is this skill's export and tells you which variant and settings they chose. Triggers on: prototype, mockup, wireframe, design options, variations, vet the UI, tweak the look, TUI mockup, design handoff." argument-hint: "[what to prototype, e.g. 'settings page, 3 variants' | or paste an AI-ASSIST PROTOTYPE HANDOFF block]" ---
# Prototype
Build a throwaway-but-polished prototype the user can open by double-clicking, explore, tune, and hand back to you with a structured export. The spine is: **brief → plan variants → build one file → verify → hand over → receive the handoff → iterate or implement.**
Three ideas make this useful rather than another mockup generator:
- **Variants explore structure, dials explore feel.** Variants differ in layout, information hierarchy and primary affordance. Colors, fonts, spacing, radius, elevation and motion are live dials that work on every variant, so never spend a variant on a recolor. - **One self-contained file.** No server, no build, no dependencies, no account. It survives being emailed to a PM or designer, who can tune it and export their decision without you in the room. - **The export closes the loop.** "Export to LLM" copies a handoff block (chosen variant, changed dials, notes, pinned comments, resolved CSS variables). The user pastes it back; you read it and either iterate or implement the real thing.
## Modes: detect from the input
| Input | Mode | |---|---| | A brief, a feature, a page, "what should this look like", "show me options" | **Build** (this is the bullseye) | | "add a variant", "make B denser", "tweak the prototype", an existing `prototypes/*.html` mentioned | **Iterate** | | A pasted block starting with `AI-ASSIST PROTOTYPE HANDOFF` or JSON with `"schema": "ai-assist-prototype/handoff@1"` | **Receive** (see "Receiving a handoff") |
## What you produce
- `prototypes/<slug>.parts.html`: the source you author. A JSON manifest plus one `<template data-variant="…">` per variant. Small, readable, diffable. - `prototypes/<slug>.html`: the deliverable, assembled by `scripts/build-prototype.mjs` from the parts file and the harness in `assets/template.html`. Never hand-copy or retype the harness; it is large and must stay intact.
Default location is `prototypes/` at the project root (create it). Put it next to the feature instead if the repo clearly organizes design artifacts elsewhere, and follow an explicit user path over either.
The built file contains the **Design Deck**, a draggable floating panel that:
- flips between variants (◀ ▶, or ← → keys), and between screens inside a variant when the variant declares them - offers vibe presets (Neutral, Calm, Bold, Editorial, Playful, Technical, Midnight, Mono, plus any you add) and ~25 dials: Feel macros (warmth, energy), Type (display/body fonts from a curated Google Fonts list, base size, scale, line height, tracking, weights), Color (light/dark, accent hue/sat/light, secondary hue shift, neutral hue/tint, surface depth, contrast), Shape (radius, border, elevation), Space (density, container width), Motion, and any custom controls the manifest adds - previews at Fit / 390 / 820 / 1280 / 1536 widths (each variant is its own document, so real media queries respond) - collects notes and click-to-pin comments on elements, saves snapshots to compare looks, and persists everything in `localStorage` per prototype - **Export to LLM** copies the handoff block; JSON copies only the JSON; View shows it for manual copy when the clipboard is blocked
TUI prototypes use the same file and deck with a terminal-specific dial set (theme, font, columns/rows, border glyphs, cursor, CRT scanlines).
## Step 1: Get the brief (fast)
Pin these down, from `$ARGUMENTS`, the conversation, and the repo, before planning:
- **Subject and audience**: what is being designed, for whom, and the one job the screen has. - **The design question**: what the prototype should settle ("table or cards?", "wizard or single form?", "does the sidebar earn its space?"). The export carries this brief, so write it as a real sentence. - **Kind**: `web` by default; `tui` when the subject is a terminal/CLI tool (ncurses, Ink, Bubble Tea, Textual, ratatui, a curses dashboard, a CLI wizard). - **Variant count**: default 3, cap 5. Fewer when the question is narrow, never more than five (they stop being different and start being noise). - **Where to save**: default `prototypes/<slug>` as above.
Look around the repo for things that make the prototype feel like *their* product rather than a generic page: a `DESIGN.md` (the `ai-assist-design-creator` output), `tailwind.config.*`, CSS custom properties, an existing nav/header, brand name, real entity names and data shapes, existing copy. Seed the manifest `defaults` and a brand preset from them and use the real content. Say what you reused.
Ask at most one or two questions, and only ones whose answer changes the work (for example, which existing page hosts this, or web vs TUI when genuinely ambiguous). If the user is not around, state your assumptions in the plan and build anyway; a prototype that exists is easy to redirect, a questionnaire is not.
## Step 2: Plan the variants
Read `references/variant-playbook.md` for archetype menus per surface type, content rules, the quality floor and the self-critique checklist. Then write a compact plan:
| id | name | thesis (what this variant bets on) | structure in one line | |---|---|---|---| | `ledger` | Ledger | Power users scan; a dense table beats cards | top nav, KPI strip, full-width table, detail screen | | `beds` | Garden beds | Spatial grouping mirrors the real garden | sidebar of beds, card grid, detail screen | | `journal` | Journal | One thing at a time, phone-first | single column feed, sticky primary action |
Hold the set to a structural-diversity test: if two variants would look alike with the same preset applied, one of them is a recolor, so redo it with an explicit structural constraint ("no card grid", "no sidebar", "list + detail"). Decide up front which screens a variant needs (usually a main screen and one drill-in), which custom controls earn a dial (sidebar width, density of a specific table, a chart style: things a dial can express and the user will actually want to tune), and one or two brand presets.
Show the plan in chat in a few lines and proceed. If the user is present they can redirect before you build; do not block on approval.
## Step 3: Build the parts file and assemble
Read `references/token-contract.md` before writing any CSS. It lists the manifest schema, every dial, every `--pt-*` variable the dials drive, the helper classes, screens, and the `PT` bridge API. For `kind: "tui"` also read `references/tui-prototypes.md`.
Author `prototypes/<slug>.parts.html`:
```html <script type="application/json" id="pt-manifest"> { "schema": "ai-assist-prototype/manifest@1", "id": "garden-dashboard", "name": "Garden Companion · dashboard", "kind": "web", "brief": "Home screen for a garden planner. Hobby gardeners on laptop and phone. Table-first, sidebar cards, or journal feed?", "controls": "web", "defaults": { "accentHue": 140, "fontDisplay": "Fraunces" }, "extraControls": [ { "id": "sidebarWidth", "label": "Sidebar width", "group": "Layout", "type": "range", "min": 200, "max": 340, "step": 10, "default": 260, "unit": "px", "var": "--x-sidebar-w" } ], "presets": { "Garden": { "accentHue": 140, "neutralHue": 90, "radius": 12 } }, "variants": [ { "id": "ledger", "name": "Ledger", "thesis": "Dense table for scanning", "screens": [{ "id": "home", "name": "Today" }, { "id": "plant", "name": "Plant" }] }, { "id": "beds", "name": "Garden beds", "thesis": "Sidebar of beds, cards per plant", "tokens": { "radius": 16 } } ] } </script>
<template data-variant="ledger"> <style> .hero h1 { font-size: var(--pt-t-3xl); } .card { background: var(--pt-surface); border: var(--pt-border) solid var(--pt-border-color); border-radius: var(--pt-radius); padding: var(--pt-s-5); box-shadow: var(--pt-shadow-sm); } @media (max-width: 720px) { .kpis { grid-template-columns: 1fr 1fr; } } </style> <section data-screen="home" data-screen-name="Today"> … </section> <section data-screen="plant" data-screen-name="Plant" hidden> … </section> <script> PT.root.addEventListener('click', e => { const g = e.target.closest('[data-go]'); if (g) PT.go(g.dataset.go); }); </script> </template> ```
Authoring rules that make the dials and the export work:
- **Consume tokens, never hardcode the look.** Colors via `--pt-bg / --pt-surface / --pt-surface-2 / --pt-text / --pt-text-muted / --pt-border-color / --pt-accent / --pt-accent-soft / --pt-accent-2`, type via `--pt-font-display / --pt-font-body` and `--pt-t-xs … --pt-t-5xl`, spacing via `--pt-s-1 … --pt-s-9`, shape via `--pt-radius*`, `--pt-border`, `--pt-shadow-sm/md/lg`, motion via `--pt-dur-*`. Decorative illustration (a gradient thumbnail) may use accent-derived vars; the validator warns on anything else. - **Each variant is its own document.** Plain selectors are safe, `@media` queries work, the Deck's viewport buttons resize the document. Base styles and optional helpers (`.pt-container`, `.pt-card`, `.pt-btn`, `.pt-btn-primary`, `.pt-input`, `.pt-badge`, `.pt-muted`, `.pt-eyebrow`) are present; use them or style your own structure. - **Real content.** The product's words, entities and realistic quantities. No lorem ipsum, no "Item 1". Placeholder art is CSS gradients or inline SVG, never remote images. - **Light interactivity is welcome** (tabs, hover, open a detail screen, toggle a state) with in-memory data, no network, no persistence. Inline `<script>` in a template runs when that variant mounts; `PT.root` is its document, `PT.go(id)` switches screens, `PT.tokens()` / `PT.on('tokens', fn)` react to dials. - **Quality floor**: responsive at 390 / 820 / 1280, visible focus, reduced motion honored (the base styles do this), readable in both modes, no horizontal overflow (`minmax(0, 1fr)` in sidebar grids).
Assemble and validate in one command (`<skill-dir>` is the folder containing this SKILL.md):
```bash node <skill-dir>/scripts/build-prototype.mjs --parts prototypes/<slug>.parts.html --out prototypes/<slug>.html ```
The build splices your parts into the harness, sets the page title, and runs `scripts/validate-prototype.mjs` (manifest shape, every variant has a template and vice versa, self-contained, token usage lint). Fix errors; treat warnings as review notes and clear the ones that are not deliberate.
## Step 4: Verify like a design lead
1. Open it. Windows: `start "" "prototypes\<slug>.html"`; macOS: `open prototypes/<slug>.html`; Linux: `xdg-open prototypes/<slug>.html`. The file works from `file://`. 2. If you have browser automation, drive it instead of guessing: load the file (or serve the folder locally if your tool refuses `file://`), then use `window.__PT__`: `await __PT
Detalles técnicos
- Versión
- 1.0.0
- Licencia
- Unknown
- Última actualización
- 22 ago 2026
- Publicado
- 22 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-prototype, listo para publicar manualmente en X.
A practical pick for the next deck: ai-assist-prototype: Build self-contained, double-click-to-open HTML prototypes so the user can vet an interface before it gets built. One file... 88 stars https://www.openagentskill.com/skills/jparkerweb-ai-assist-prototype?ref=x
Respuesta opcional con comando de instalación
Listing + install path for ai-assist-prototype: https://www.openagentskill.com/skills/jparkerweb-ai-assist-prototype?ref=x Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-prototype
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.
Reclamar este skillReclamación del propietario
Reclamar esta ficha de skill
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.
Kit de enlaces para creadores
Añade las insignias de evidencia a tu README
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-prototype)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-prototype)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-prototype/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-prototype)Autor
jparkerweb
@jparkerweb
Etiquetas
Afinidad con plataforma
Señales de salud
- Estrellas de GitHub
- 88
- Puntuación de calidad
- 36/100
- Último push de GitHub
- 22 ago 2026
- Pistas del framework
- Desconocido
- Vistas de OpenAgentSkill
- 1
- 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 recienteActualizado hoyAprobado
- 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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