Brand asset generation

brand-asset-generation

Generate brand assets (banner, social card, CIP element) via structured prompting, brand-token injection, and provider routing. Rides on the existing pack-ai-image adapters — not a second image-gen stack.

When to use

• User asks to generate a banner, social card, header image, or CIP (corporate identity) element.
• Branded asset production where palette, typography, or voice must stay consistent.
• When brand tokens are available and should drive the visual output.
• When a brief alone (no tokens) still needs a governance-aware image output.

Procedure

1. Identify asset type and spec — determine format (banner, social card, CIP element), output dimensions (e.g. 1200×630 for Open Graph, 1080×1080 for square social), and target channel (web, print, social platform).
2. Inject brand tokens when present — if pack-brand is installed, load .tokens.json (colors, typography, voice). Feed hex values, font names, and tone keywords directly into the prompt. Without tokens, derive palette and type from the brief itself; raw generation works — output is brief-driven, not token-driven.
3. Route and prompt — delegate provider selection to image-provider-routing (text-in-image → Ideogram, photoreal product shot → Flux, etc.). Author the provider-specific prompt with the asset spec, injected tokens, and any negative constraints.
4. Dry-run and validate — invoke the adapter (scaffold-tier; see Gotcha). Confirm the returned dry-run plan matches the spec: dimensions, style intent, brand token usage.
5. Rights and AI-disclosure governance — run image-likeness-and-rights if the asset depicts a real person or brand mark. Attach the AI-generation disclosure footer per media-governance-routing before delivering output.

Output format

1. Asset spec — type, dimensions, channel, and routing rationale (which provider and why).
2. Prompt — final provider-specific prompt string with injected brand tokens (or brief-derived palette/type if no tokens). Include key params: aspect ratio, style keywords, negative prompts.
3. Adapter invocation / dry-run note — the dry-run plan returned by the adapter, or an explicit note: "adapter is experimental (scaffold-tier) — dry-run plan only; no rendered asset until promotion per provider-lifecycle-discipline."
4. Governance confirmation — rights check result and AI-disclosure footer.

Gotcha

• Without a brand token layer the output is generic — feed the brief's exact palette (hex codes) and typography (font names or style descriptors) into the prompt. Vague color terms ("blue", "modern") produce inconsistent results. Brand tokens from pack-brand (Phase B of the brand pipeline) eliminate this gap; until that pack ships, rely on brief-supplied values.
• Brand tokens come from pack-brand (Phase B) — this skill consumes tokens; it does not author them. If .tokens.json is absent, proceed brief-driven and note the gap.
• Adapters are scaffold-tier (dry-run only) — all pack-ai-image adapters are experimental. This skill produces a blueprint and dry-run confirmation; actual renders require a maintainer to capture a smoke trace and promote the adapter to stable.

Do NOT

• Do NOT invent brand colors or voice — use tokens from .tokens.json or explicit values from the brief. Guessing palette values produces off-brand output.
• Do NOT omit the AI-generation disclosure — every delivered asset requires the disclosure footer per media-governance-routing, regardless of how generic the output appears.
• Do NOT claim a rendered asset is produced while adapters are scaffold-tier — surface the dry-run caveat explicitly every time.

See also

• logo-generation — logo-specific generation with vector and mark constraints.
• image-generation — general-purpose image generation end-to-end.
• image-provider-routing — select the right provider before writing the prompt.
• image-likeness-and-rights — rights check before generating real-person likenesses or brand marks.