generate-mockups
Generate visual mockups of the finished hardware project using fal.ai's nano-banana (Gemini 2.5 image) model.
Skill by danielrosehill
Install
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
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: design, data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
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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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- 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
- Source
- GitHubgithub-graphql
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Cite this page
generate-mockups skill. Agent Mart. https://agentmart.dev/skills/danielrosehill-generate-mockups (last updated 2026-10-24)