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generate-mockups

Generate visual mockups of the finished hardware project using fal.ai's nano-banana (Gemini 2.5 image) model.

Skill by danielrosehill

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/danielrosehill-generate-mockups

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About

Generate visual mockups of the finished hardware project using fal.ai's nano-banana (Gemini 2.5 image) model. Useful for early-stage visualisation, communicating intent to collaborators, or scoping enclosure design before any parts arrive.

Use cases: design, data

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/generate-mockups

What's inside

Skill name
generate-mockups
Description
Generate visual mockups of the finished hardware project using fal.ai's nano-banana (Gemini 2.5 image) model. Useful for early-stage visualisation, communicating intent to collaborators, or scoping enclosure design before any parts arrive.
License
MIT
Instructions
36 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Generate Mockups

Produce AI-generated mockup images of a project from its written spec.

## Prerequisites

- The fal.ai MCP server is available (`mcp__*__fal__run_model` or equivalent), or the user has a `FAL_KEY` and we can call the HTTP API directly.
- A project with `spec.md` exists.

## Flow

1. **Build the prompt** from `spec.md`. Include:
   - Form factor (handheld / desk-mounted / wall-mounted / outdoor enclosure / wearable).
   - Key visible elements (display, buttons, sensors poking out, antennas, LEDs, connectors).
   - Material / finish hint (3D-printed PLA, machined aluminium, laser-cut acrylic, custom PCB visible).
   - Style hint (clean product render, exploded view, lifestyle shot, technical schematic-style).
   - Negative prompt — no text overlays, no logos, no people unless requested.
2. **Pick the model** — default to `fal-ai/nano-banana` (text-to-image). For variations of an existing image, use `fal-ai/nano-banana/edit`. Both are fast and cheap, suitable for rapid iteration.
3. **Generate 2–4 candidates** in parallel with slight prompt variations (different angles or styles) so the user has options.
4. **Save the images** to `<projects_dir>/<slug>/mockups/` with names like `mockup-<timestamp>-<variant>.png`. Save the prompt used alongside in `mockups/prompts.md` so the user can iterate.

## Output

- Files written to `<projects_dir>/<slug>/mockups/`.
- A summary line in the conversation showing each saved file and the variant description.

## Iteration

If the user wants tweaks ("make it smaller", "show it mounted on a wall", "battery should be visible"), use `fal-ai/nano-banana/edit` with the previous best image as input rather than starting from scratch — preserves the bits that worked.

## Caveats

- Mockups are illustrative, not engineering drawings. Don't claim dimensional accuracy. They're for communication / inspiration, not fabrication.
- The model will sometimes invent components that aren't in the BOM. Note any discrepancies for the user when presenting candidates.

From danielrosehill/Claude-Hardware-Spec-Assembly-Plugin, MIT.

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Last commit (this folder)
Apr 30, 2026 (6 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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generate-mockups skill. Agent Mart. https://agentmart.dev/skills/danielrosehill-generate-mockups (last updated 2026-10-24)