Higgsfield Brandkit

Higgsfield Brandkit

Build a coherent identity and its requested applications. Treat supplied brand facts and official assets as fixed constraints.

Bootstrap

1. Resolve SKILL_ROOT to this skill's installed directory and create a durable project directory:

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   BRANDKIT_WORKDIR="${PWD}/brandkit"
   BRANDKIT_STATE="${BRANDKIT_WORKDIR}/state.json"
   mkdir -p "${BRANDKIT_WORKDIR}"

2. Read prerequisites. Check tools before the stage that needs them. Never install system packages without the user's permission.

3. If higgsfield is missing, install it only after permission:

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   curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

4. If higgsfield account status fails with an authentication or workspace error, ask the user to run higgsfield auth login or select a workspace, then wait.

5. Inspect live model contracts before paid generation:

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   higgsfield model get recraft_v4_1 --json
   higgsfield model get seedream_v5_pro --json
   higgsfield model get gpt_image_2 --json

CLI mapping

Local image paths passed with --image are auto-uploaded. Keep HTML, SVG, PPTX, and PDF deliverables as local project files unless the user explicitly needs a hosted copy.

User-facing behavior

• Match the user's language. Keep Design Brain reasoning, prompts, state mechanics, scripts, model lookup, and QA internals private.

• Send at most one short status sentence per visible generation batch, then stay quiet until the result is ready.

• Ask one compact set of only unresolved blocking questions. Never repeat facts or force a complete identity questionnaire for a partial task.

• After each palette, logo, typography, or downstream review, stop and wait for ordinary user feedback.

• Never infer approval from silence, successful generation, or your own preference.

• Preserve exact user copy. Never invent positioning, values, claims, ingredients, prices, certifications, statistics, or regulatory content.

Core workflow

1. Classify the request.

   • apply-existing: use supplied official assets without redesigning them.

   • extend-partial: create only missing slots required by the requested output.

   • create-identity: create a new logo or identity only when explicitly requested.

2. Read state. Run:

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   python3 "$SKILL_ROOT/scripts/brandkit.py" state \
     --state-file "$BRANDKIT_STATE" --action get_status

   Local state is durable. Never paste, hand-edit, or recreate approvals when the state file exists.

3. Run intake and asset analysis. Read intake, asset analysis, state routing, and exact state payloads. Lock every user-declared official logo, palette, and typography slot immediately.

4. Create the Brand Lock. Read Brand Lock. Record exact spelling, official assets, colors, fonts, layout/shape rules, requested outputs, and forbidden treatments.

5. Require only the slots the output uses.

   • logo-only → palette + logo for a new mark; official logo alone for an existing mark

   • palette-only → palette

   • typography-only → typography

   • copy-free mockup/merch → logo; add palette only when color/application requires it

   • text-bearing social/packaging/poster/signage → logo + palette + typography

   • Brandbook/deck → logo + palette + typography

6. Build missing foundation slots. Read Design Brain, concept boards, inline reviews, and only the needed palette, logo, or typography module.

7. Continue the original request as soon as its required slots are approved. Never ask the user to choose scope again.

8. Load only the requested production module:

   • mockups

   • social graphics

   • posters/banners

   • packaging

   • signage

   • merchandise

   • presentation decks

   • Brandbooks

9. QA and approval. Read QA and iteration. Repair only the failing output. Save a downstream element only after explicit approval with its exact foundation dependencies.

New identity sequence

1. Palette

Render 2–3 exact palette options as deterministic HTML using preview payloads. Show PNG screenshots plus editable HTML files and wait. Persist the selected palette with approve_palette before logo generation.

2. SVG logo marks

Read logo prompt enhancer. Produce exactly three distinct symbol-only mechanisms and one Recraft prompt for each. Write each long prompt to a file and submit separately:

higgsfield generate create recraft_v4_1 \
  --model_type vector \
  --colors @"${BRANDKIT_WORKDIR}/logo-colors.json" \
  --background_color '#F7F7F5' \
  --aspect_ratio 1:1 \
  --resolution 2k \
  --wait --json < "${BRANDKIT_WORKDIR}/logo-candidate-1.txt"

Use the returned SVG URLs directly for review. After selection, inspect the exact SVG without altering it:

python3 "$SKILL_ROOT/scripts/brandkit.py" logo-inspect \
  --source "<selected Recraft SVG URL or absolute local path>"

Persist the exact job ID, SVG URL, name, palette revision, and returned canonical geometry fingerprint with approve_logo.

3. Typography

Propose 2–3 unique display/body pairs using supplied fonts or verified Google Fonts. Render the real brand name and sample copy through the preview script. Persist only the selected pair with approve_typography.

Interactive flows always stop for palette, logo, and typography selections. Explicit no-question mode may choose and persist a palette, but it still shows all three SVG logo candidates and stops for the user's logo selection; exact brand marks are never self-approved.

Consistency invariants

• Reuse the same approved logo source everywhere. Never redraw an official or selected SVG when deterministic placement/export is possible.

• A generated logo depends on the palette revision used to create it. Changing that palette invalidates the generated logo and its dependents; changing typography does not invalidate the symbol mark.

• Changing a foundation slot invalidates only downstream elements that list that slot in required_slots.

• Copy the same Brand Lock values into every related generation prompt: exact hex, font roles, shape language, placement, clear space, composition, and forbidden treatments.

• Use Recraft V4.1 vector mode only for new logo marks.

• Use Seedream as the primary photoreal mockup generator. Use GPT Image 2 only for the controlled stage that adds readable text or exact graphic details.

• Use local deterministic SVG/PPTX/HTML construction for exact copy and editable layouts. Do not ask an image model to fake editable files.

• Do not promise native Figma, Canva, PSD, AI, or EPS files.

Deterministic scripts

Create JSON input files under "$BRANDKIT_WORKDIR"; never interpolate user text directly into shell arguments.

python3 "$SKILL_ROOT/scripts/brandkit.py" preview \
  --input "$BRANDKIT_WORKDIR/reviews.json" \
  --output-dir "$BRANDKIT_WORKDIR/reviews"

python3 "$SKILL_ROOT/scripts/brandkit.py" logo-export \
  --input "$BRANDKIT_WORKDIR/logo-export.json" \
  --output-dir "$BRANDKIT_WORKDIR/logo"

python3 "$SKILL_ROOT/scripts/brandkit.py" brandbook-build \
  --state-file "$BRANDKIT_STATE" \
  --input "$BRANDKIT_WORKDIR/brandbook.json" \
  --output-dir "$BRANDKIT_WORKDIR/brandbook"

For logo export, load logo export payloads. For Brandbooks, use the bundled builder only; never substitute an improvised PowerPoint or PDF generator after a deterministic contract failure.

Failure policy

• Retry a failed Recraft or image-generation request once with the same locked concept and corrected contract. Stop after the second equivalent failure.

• If preview or logo export fails twice, report the concrete error; never replace it with ad-hoc SVG rewriting.

• If the Brandbook template, font, or conversion contract fails, stop immediately. Do not produce a visually different fallback and call it canonical.

• If exact typography or official-logo fidelity cannot be preserved, disclose the limitation instead of claiming completion.

• Never expose raw auth tokens or credentials in files, logs, or chat.

Delivery

For Brandbooks, follow the strict response contract in brandbook: PPTX link/path, PDF link/path, and font-install warning only.

For other outputs return:

1. The requested visual files and previews.

2. A compact Brand Lock summary.

3. Editable versus flattened format labels.

4. Required-font/import limitations.

5. Stable variant names for targeted revisions.

Reference index

• Prerequisites — stage-specific local dependencies and install commands.

• Intake — minimal questions and input routing.

• Asset analysis — official/reference classification and measurement.

• State routing and state payloads — persistent approvals.

• Brand Lock — canonical visual constraints.

• Design Brain — private art direction.

• Concept boards, preview payloads, and inline reviews — selection stages.

• Logo, logo prompt enhancer, and logo export payloads — SVG generation and deterministic variants.

• Palette and typography — foundation slots.

• Mockups, social graphics, posters/banners, packaging, signage, and merchandise — applications.

• Presentation decks and Brandbooks — editable documents.

• QA and iteration — preflight, repair, approval, and delivery manifest.