| name | saas-visual-generator |
| description | Generate brand visuals via the Higgsfield MCP — logo variants, moodboard tiles, and a brand-guidelines document — once the brand intake (`brand.json` + `saas-context.json`) exists. Auto-activate after `saas-brand-intake` finishes, or when the user says "generate logo", "make moodboard", "create visuals", `/generate-visuals`, `/regen-logo`, `/regen-moodboard`. Never fall back to other image generators if Higgsfield is unavailable — stop and report. |
SaaS Visual Generator
You are Step 2 of the flow. You turn brand.json + saas-context.json into actual visual assets via the Higgsfield MCP and write a brand-guidelines.md.
Inputs (must exist)
brands/<slug>/brand.jsonbrands/<slug>/saas-context.json
If either is missing, hand back to saas-brand-intake.
Outputs (final state after step 2 completes)
brands/<slug>/
├── assets/
│ ├── logo/
│ │ ├── v1/color.png
│ │ ├── v2/color.png
│ │ ├── v3/color.png
│ │ └── <primary>/ # only the user-picked variant gets crops
│ │ ├── color.png # (same as the draft above)
│ │ ├── mono.png
│ │ └── favicon.png
│ └── moodboard/ # brand identity board (9 tiles)
│ ├── 01-logo-primary.png # uses the picked logo as image input
│ ├── 02-logo-dark.png # uses the picked logo as image input
│ ├── 03-app-icon.png # derived from the picked logo
│ ├── 04-color-palette.png # swatches with exact hex labels
│ ├── 05-typography.png # display + body specimen
│ ├── 06-avatar-favicon.png # picked logo at 4 sizes
│ ├── 07-ui-system.png # buttons + form preview
│ ├── 08-direction.png # photography / illustration direction
│ └── 09-stationery.png # picked logo on business card
├── brand-guidelines.md # editable source (focused on picked primary only)
├── brand-guidelines.html # intermediate render
└── brand-guidelines.pdf # ◄ THE SHIPPING DELIVERABLE
All image generation uses gpt_image_2 (locked) — see ../higgsfield-recipes/prompts.md for the model selection and default params.
Flow shape (token-efficient)
2a. Generate 3 logo COLOR drafts only (3 calls)
2b. User picks primary via AskUserQuestion (0 calls — just a prompt)
2c. Generate mono + favicon for ONLY picked (2 calls)
2d. Generate 9-tile identity board, with the
picked logo passed as `medias` reference (9 calls)
2e. Extract palette + type, write guidelines (0 calls)
------
14 calls total
Old flow was 22 calls (4 logos × 3 crops + 9 tiles + 1 hero poster). The hero poster moved to step 4. Step 2 alone went from 21 → 14 image calls. ~33% credit savings AND the identity board feels far more cohesive because the tiles reference the EXACT picked logo, not a "logo for X" description.
How to generate
2a. Logo drafts — 3 color variants only
For each variant, call mcp__higgsfield__generate_image once (color only — no mono, no favicon yet):
- Prompt built from
brand.json (name, mood, color anchors, logoType, tone) — see logo-prompts.md.
- Distinct approach per variant — variants must be meaningfully different, not minor tweaks:
- v1 — Most literal interpretation of the chosen
logoType
- v2 — More geometric / structured (or expressive / illustrative — whichever contrasts v1)
- v3 — Reductive / minimal alternative
Save under brands/<slug>/assets/logo/v<n>/color.png. That's 3 image calls total.
2b. User picks the primary — HARD PAUSE
Stop and ask the user. Use AskUserQuestion:
{
"question": "Which logo should be the primary? I'll generate mono + favicon crops and the identity board around it.",
"header": "Pick logo",
"options": [
{ "label": "v1 — <one-line intent>", "description": "<image-relative path>" },
{ "label": "v2 — <one-line intent>", "description": "<image-relative path>" },
{ "label": "v3 — <one-line intent>", "description": "<image-relative path>" },
{ "label": "Regenerate one of them", "description": "Tell me which variant to redo and what to change" }
],
"multiSelect"
Do NOT proceed past this step until the user picks (or asks to regenerate). If they want a regen, route through /regen-logo v<n> for the one variant only — never redo all three.
Once the user picks, write the choice to brands/<slug>/approval.json:
{
"approved": false,
"primaryLogo": "v2",
"primaryPickedAt": "<iso>"
}
approved stays false — the approval gate (Step 3) covers the assembled brand, not just the logo.
2c. Crops for the picked variant only
For the picked <primary> (e.g. v2):
- Generate
mono.png — same prompt with "single-color version, pure black on white, no gradients". Save to brands/<slug>/assets/logo/<primary>/mono.png.
- Generate
favicon.png — same prompt with "tight square crop, just the central mark, optimized for 32×32 legibility, no background". Save to brands/<slug>/assets/logo/<primary>/favicon.png.
2 image calls total. The other (un-picked) variants stay color-only as drafts.
2d. Brand identity board — 9 tiles, with the picked logo as input
This is not a vibes-only Pinterest board. It's a real brand identity board — the kind a brand studio would ship. Every tile leans into gpt_image_2's strength at text-in-image (hex labels, type specimens, button labels, brand name).
First, upload the picked logo as a media input so the tiles can reference the actual artwork:
- Call
mcp__higgsfield__media_upload with the path brands/<slug>/assets/logo/<primary>/color.png.
- Call
mcp__higgsfield__media_confirm to finalize.
- Capture the returned media UUID — pass it as
medias: [{ value: "<uuid>", role: "image" }] on tiles that feature the logo.
Then call mcp__higgsfield__generate_image once per tile (all model: "gpt_image_2"):
| # | Tile | Uses logo input? |
|---|
| 01 | 01-logo-primary.png — canonical lockup on neutral surface | ✓ |
| 02 | 02-logo-dark.png — logo on dark/inverse surface | ✓ |
| 03 | 03-app-icon.png — rounded-square app icon on a phone home screen | ✓ |
| 04 | 04-color-palette.png — 5 swatches with exact hex code labels | ✗ |
| 05 | 05-typography.png — display + body specimen with sample pitch | ✗ |
| 06 | 06-avatar-favicon.png — mark at 4 sizes (256 / 64 / 32 / 16) | ✓ |
| 07 | 07-ui-system.png — primary button "Join the waitlist" + secondary + input | ✗ |
| 08 | 08-direction.png — photography or illustration direction | ✗ |
| 09 | 09-stationery.png — business card or email signature in context | ✓ |
See moodboard-prompts.md for the full prompt patterns + aspect ratios per tile + which ones pass the logo medias.
2e. Palette + typography extraction
After generating, look at the moodboard and propose:
- A 5-color palette with
role (primary, accent, neutral-bg, neutral-fg, warning/cta), hex, usage notes.
- A 2-family typography pairing (display + body). Recommend specific fonts (Google Fonts or system-safe).
2f. Write brand-guidelines.md (editable source)
Use guidelines-template.md as the structure. Fill in:
- Logo lockup paths (relative to the brand folder)
- Color palette
- Typography
- Voice & tone (from
brand.json)
- Visual personality (one paragraph synthesizing mood + palette)
- Moodboard tile list with one-line notes each
2g. Render brand-guidelines.pdf — the shipping deliverable
The PDF is the canonical brand guidelines artifact — the file the founder shares with engineers, designers, marketers, investors. It's designed (not "markdown printed to PDF"), brand-aware, focused entirely on the user-approved primary logo.
Steps:
-
Write the HTML. Use templates/brand-guidelines.html.hbs as the template. Interpolate ONLY the picked primary logo's paths (approval.json.primaryLogo's color.png / mono.png / favicon.png), the palette extracted in 2e, the typography pairing, the 9 identity-board tiles, and the voice & tone from brand.json. Save to brands/<slug>/brand-guidelines.html.
The HTML CSS variables (--c-primary, --c-accent, --font-display, --font-body) MUST be filled with the actual brand palette + typography pairing — the PDF inherits the brand's identity.
-
Use relative paths inside the HTML. Images reference paths like assets/logo/v2/color.png and assets/moodboard/01-logo-primary.png — relative to the HTML file's own directory. Do NOT embed base64 — keeps the file small and lets the user swap assets without re-rendering.
-
Render to PDF. Run:
"${CLAUDE_PLUGIN_ROOT}/tools/html-to-pdf.sh" \
"brands/<slug>/brand-guidelines.html" \
"brands/<slug>/brand-guidelines.pdf"
The script uses Chrome/Chromium headless. If it's missing, the script exits with a clear install hint — surface that to the user verbatim.
-
Verify. PDF must exist and be > 50 KB (cover + asset embeds). Open size check via stat. If empty, debug the HTML in a browser first, then retry.
-
Keep the MD. brand-guidelines.md stays as the editable source. brand-guidelines.pdf is the deliverable.
End-of-step messages
After 2a (3 color drafts ready)
"Generated 3 logo drafts at brands/<slug>/assets/logo/v1..v3/color.png. Pick one and I'll generate the rest (mono, favicon, identity board) around it."
Then immediately call AskUserQuestion per step 2b.
After 2d (identity board ready)
"Logo <primary> is finalized, identity board is at brands/<slug>/assets/moodboard/. Rendering brand guidelines PDF now."
After 2g (PDF ready)
*"Brand guidelines deliverable ready:
brands/<slug>/brand-guidelines.pdf — the shipping artifact (PDF, designed)brands/<slug>/brand-guidelines.md — editable sourcebrands/<slug>/brand-guidelines.html — intermediate render
Reply /approve-brand to continue, or tell me what to change. (/regen-moodboard 02 for one tile, or say "switch primary to v3" to re-pick.)"*
Regeneration commands
/regen-logo <variant> — re-generate one logo variant only (color draft). Variant id is v1, v2, or v3./regen-moodboard <slot> — re-generate one tile only. Slot id like 02.- "switch primary to v3" — re-pick the primary; agent regenerates crops + identity tiles that referenced the old logo.
- "redo all" or
/generate-visuals — full re-run from scratch.
Hard rules
- Higgsfield MCP only. If
mcp__higgsfield__* tools are unavailable or return an auth error, stop and tell the user:
"Higgsfield MCP is not authenticated. Run /mcp and authenticate higgsfield, then retry."
- No placeholder assets. Don't generate SVG logos by hand. Don't use stock images.
- No moodboard from text. Each tile is a real generated image.
- Check balance first. Call
mcp__higgsfield__balance once at the start. If the user has low/zero credits, surface that before running.
Delegation
The full step-2 run (3 color drafts → user pick → 2 crops → 9 identity tiles = 14 image calls, all gpt_image_2) can be delegated to agents/visual-generator.md to keep the main context light. The agent runs 2a as a single batch, hands the pick decision back to the main agent (which calls AskUserQuestion), then resumes for 2c–2f once the choice is in.
See also
