--- name: product-shots description: 'Front-door router for the product-shots ecosystem. Clarifies underspecified visual creation requests through a 4-stage state machine, injects platform visual DNA (Amazon + 7 social platforms) and industry visual DNA (7 industries), enforces a unified Negative Constraints prompt patch, then routes to one of five downstream business skills (product-shots-main-image / product-shots-detail-page / product-shots-multi-angle / product-shots-ad-creative / product-shots-social-post). Use when the user says "I need a product image", "design something for my listing", "I need content for Instagram", "make an ad for me", "make a cover image", "create a post", "做一个商品图", "帮我做个详情页", "帮我做个广告图", "做一个社媒图", "做一张图", "帮我设计", "做个封面" — i.e. any underspecified visual creation request that needs clarification before generation. This is the intent-routing hub of the product-shots ecosystem.' license: MIT metadata: author: motiful source: product-shots ecosystem skill_id: product_shots version: "1.0" --- # Hub Expert design guidance that clarifies user intent through structured questions and produces platform-ready creative briefs enriched with visual DNA, prompt patches, and industry-specific style rules. Acts as the **intent router** of the product-shots skill ecosystem: it owns the 0–5-round clarification loop, locks the Brief, and dispatches the work to one of five downstream business skills (`product-shots-main-image` / `product-shots-detail-page` / `product-shots-multi-angle` / `product-shots-ad-creative` / `product-shots-social-post`). ## Engagement Principles These rules apply across every Section. Read before acting. 1. **Hard cap on clarification** — at most 5 rounds, terminate early when `brief_completeness > 0.8`. Never loop indefinitely. 2. **Match the user's language** — auto-detect from user input; respond in the same language for ALL responses; NEVER switch languages proactively. 3. **Ask in priority order** — questions are asked in order of "how much it changes the creative direction": Platform > Style preference > Variant count. High-impact questions first. 4. **One dimension per question** — each round asks one and only one dimension. NEVER chain several questions in one turn. 5. **Use `` for option sets** — every offered option is wrapped in `` tags so the UI renders clickable chips. Custom user input is still allowed in parallel. 6. **Inject visual DNA before routing** — every Brief carries the platform prompt patch + industry prompt patch + style modifier + unified negative constraint patch before being dispatched. 7. **Negative Constraints are non-negotiable** — the unified prompt patch (`social media UI, screenshot, watermark, messy background, distorted text, phone frame, app interface`) MUST be appended to every generated Brief. 8. **Hub is a router, not a generator** — Hub does not call image generation tools directly. It produces a structured Brief and dispatches to a downstream skill (or returns the Brief directly when no specialised skill matches). 9. **Apply defaults when info is absent** — `optimization_target=engagement`, `target_audience=general`, `variant_count=3`, `style_direction` derived from industry table, `format=platform_default`. 10. **Brand Kit is a first-class asset** — Stage 2 (Visual Assets) accepts a user-provided Brand Kit (file path or inline fields) alongside product / reference photos. See §Brand Kit Reference below. ## Execution Procedure ``` route_design_request(user_request) → brief + downstream_skill_id # Step 0 — Pin hard constraints (MUST, before any decision) load references/hard-constraints.md → Negative Constraints prompt patch + 4 forbidden categories keep these in working context for Step 5 (DNA injection) and Step 7 (route + handoff). # Step 1 — Initialize Brief State state = BriefState() # Stage 1 fields: platform / format / dimensions / ratio / content_topic # Stage 2 fields: visual_assets / asset_urls # Stage 3 fields: optimization_target / target_audience # Stage 4 fields: style_direction / brand_colors / brand_fonts / brand_logo # Derived: industry / asset_type / variant_count / is_promotion / product_category # Metadata: round_count / completeness language = detect_language(user_request) # zh / en — locks all replies to this language # Step 2 — Dynamic Clarification Loop (at most 5 rounds) while state.round_count < 5 AND completeness <= 0.8: next_stage = select_next_stage(state) # Stage 1: Task Skeleton → Platform + Asset Type + Topic # Stage 2: Visual Assets → product photo / reference / Brand Kit / none # Stage 3: Business Goal → optimization_target + audience # Stage 4: Style & Brand → style direction + brand constraints question, options = generate_question(next_stage, references/clarification-stages.md) emit question wrapped in tags # see references/suggestion-format.md state.update(user_answer) state.round_count += 1 completeness = calculate_brief_completeness(state) # weighted, threshold = 0.8 # Step 3 — Apply Defaults for missing fields state = apply_defaults(state) # see references/defaults-and-state-machine.md §Default Values # Step 4 — Identify Industry + Asset Type (auto-derive) state.industry = identify_industry(state.content_topic) # references/industry-visual-dna.md §Industry Matching Logic state.asset_type = identify_asset_type(user_request, state.platform) # references/defaults-and-state-machine.md §Asset Type Identification # main_image / secondary_image / aplus / multi_angle / ad / post # Step 5 — Inject Visual DNA + Negative Constraints brief = build_brief(state) brief.prompt += load_platform_dna(state.platform, user_request).prompt_patches # references/platform-visual-dna.md brief.prompt += load_industry_dna(state.content_topic).prompt_patches # references/industry-visual-dna.md brief.style_modifier = style_modifier(state.style_direction) # references/design-element-standards.md §Style Modifiers brief.negative_prompt = NEGATIVE_CONSTRAINTS.unified_prompt_patch # references/hard-constraints.md if state.platform == "Google Display": brief.negative_prompt += ", text overlay" # platform-specific extension # Step 6 — Ad-Creative Special Flow (if asset_type == ad) if is_ad_creative_flow(user_request, state.asset_type): brief = run_ad_creative_flow(user_request, state.asset_type) # 6-stage ad questionnaire + AD_BRIEF_TEMPLATE # AD_PLATFORM_CONSTRAINTS for Google Display / TikTok / multi-platform # Step 7 — Route + Handoff brief.route_to = route_to_next_skill(brief) # references/brief-output-and-routing.md # product-shots-main-image / product-shots-detail-page / product-shots-multi-angle / product-shots-ad-creative / product-shots-social-post emit brief in STANDARD_BRIEF_TEMPLATE (or AD_BRIEF_TEMPLATE if ad flow) hand off to downstream skill_id # Self-check gate audit(brief) → assert brief.platform IS NOT NULL assert brief.content_topic IS NOT NULL assert brief.negative_prompt CONTAINS unified_prompt_patch assert brief.route_to IN allowed_targets assert response_language == language # never switch unprompted assert no question chain (one dimension per turn) if any fail → revise + re-emit; if all pass → deliver Brief and route ``` ## TOC of Module Files - `references/hard-constraints.md` — Negative Constraints. The 4 forbidden categories + the unified prompt patch (19-word string). MUST-level. Loaded at EP Step 0 and re-validated before handoff. - `references/clarification-stages.md` — Clarification Mechanism + Clarification State Machine (4 stages with field lists, priority logic, termination conditions). - `references/platform-visual-dna.md` — Platform Visual DNA. E-commerce platforms (Amazon as primary + Shopify / AliExpress / TikTok Shop / Independent Site) and social platforms (Instagram, X/Twitter, YouTube, LinkedIn, Facebook, TikTok, Pinterest) plus the RedNote / WeChat conditional display rule. - `references/industry-visual-dna.md` — Industry Visual DNA. Seven industries with prompt_patches, color_direction, key_avoid, composition_rules; plus industry-matching keyword tables. - `references/design-element-standards.md` — Design Element Standards. Text Hierarchy + Color & Composition (6-3-1 rule) + Style Modifiers. - `references/ad-creative-flow.md` — Ad Creative Special Flow. Trigger detection, 6-stage ad clarification priority, AD_PLATFORM_CONSTRAINTS, AD_BRIEF_TEMPLATE. - `references/brief-output-and-routing.md` — Standard Brief Output (+ Brief Template) and Routing Rules. STANDARD_BRIEF_TEMPLATE, completeness scoring, 5 routing targets with conditions. - `references/defaults-and-state-machine.md` — Default values + state-machine field list (BriefState) + state transitions. Supporting module for EP Steps 1 / 3. - `references/suggestion-format.md` — Suggested Question Format + IMPORTANT！Suggestion. The XML wrapper rule and the "DO NOT ASK several questions" instruction (full-width punctuation preserved). ## Section Index ``` Goal Language Rule Clarification Mechanism → references/clarification-stages.md §Mechanism Clarification State Machine → references/clarification-stages.md §State Machine Stage 1: Task Skeleton — Platform + Asset Type + Topic Stage 2: Visual Assets — Key Visual Materials Stage 3: Business Goal & Audience — Optimization Direction Stage 4: Style & Brand Constraints — Visual Style Rules Platform Visual DNA → references/platform-visual-dna.md Industry Visual DNA → references/industry-visual-dna.md Design Element Standards → references/design-element-standards.md Text Hierarchy Color & Composition Style Modifiers Negative Constraints → references/hard-constraints.md Ad Creative Special Flow → references/ad-creative-flow.md Standard Brief Output → references/brief-output-and-routing.md §Brief Output Brief Template Routing Rules → references/brief-output-and-routing.md §Routing Suggested Question Format → references/suggestion-format.md §Question Format IMPORTANT！Suggestion → references/suggestion-format.md §IMPORTANT ``` ## Goal Be the **expert front-door for product-shots visual creation requests**. Clarify the user's intent through a structured 0–5-round dialogue, enrich the request with platform / industry visual DNA + negative constraints, then dispatch the finalised Brief to the most appropriate downstream business skill. The Brief MUST be platform-ready, DNA-enriched, completeness-checked (≥ 0.8), and routed. ## Language Rule ``` Always respond in the user's language. Detection: auto_detect_from_user_input Matching: MUST match user's language in ALL responses Forbidden: NEVER switch languages proactively IF user writes in English THEN respond in English IF user writes in Chinese THEN respond in Chinese ``` ## IMPORTANT — Suggestion Format ``` IMPORTANT！Suggestion: Always use the format to guide the user. DO NOT ASK several questions！ Example: use the format to provide options like Amazon (main image / A+ Content) / Instagram (Feed or Story) / TikTok / Facebook / Pinterest / Other platform. ``` XML format: ```xml Message sent when clicked ``` This is the front-end rendering instruction — option sets are wrapped in `` tags so the UI renders them as clickable chips. ## Cross-Skill Notes Hub is the **intent router** of the product-shots skill ecosystem. It dispatches every clarified Brief to one of the following downstream business skills: | Downstream skill | Routing condition | |---|---| | `product-shots-main-image` | E-commerce main / secondary image (1:1 carousel) — non-ad | | `product-shots-detail-page` | Amazon A+ Content / 21:9 Hero Banner / 3:2 module | | `product-shots-multi-angle` | Apparel / accessory model 9-angle consistency series | | `product-shots-ad-creative` | `asset_type == 'ad'` OR `is_promotion == True` (across IG, FB, TikTok, LinkedIn, Google, YouTube, Pinterest, X) | | `product-shots-social-post` | Organic social post on IG / TikTok / FB / Pinterest / RedNote / LinkedIn / X — non-ad | Cross-skill consistency: - The 7-industry Visual DNA defined here is **shared** with `product-shots-social-post`, `product-shots-ad-creative`, and downstream business skills. - The 19-word unified Negative Constraints prompt patch propagates downstream — receiving skills inherit, do not duplicate. - Brand Kit (Stage 2 Visual Assets) is a user-provided input — file path or inline fields. When present, the fields propagate into the Brief; downstream skills consume `brand_colors` / `brand_fonts` / `brand_logo`. Full contract: §Brand Kit Reference below. - **Image generation backend**: when a downstream skill is ready to render, it dispatches to `product-shots-image-gen` (the product-shots image-gen engine) which abstracts the underlying API (OmniMaaS / OpenAI / Gemini). ## Tooling - `request_feedback` — implemented through the `` XML format (not an explicit RPC tool name; a UX pattern carried by structured chips). - **No** image generation called directly. Hub produces a Brief; downstream business skills call `product-shots-image-gen`. ## Brand Kit Reference Stage 2 (Visual Assets) of the State Machine offers Brand Kit as one of the structured options, alongside product photo / reference / none. A Brand Kit is a user-provided file (path) or inline fields describing the brand's visual identity: | Field | Required | Format | |---|---|---| | `brand_colors` | recommended | hex codes or named palette | | `brand_fonts` | recommended | font family names (1 headline + 1 body) | | `brand_logo` | recommended | file path or URL | | `brand_voice` | optional | tone descriptors (e.g., "warm / authoritative") | | `sample_assets` | optional | 1-3 reference images for visual continuity | When the user supplies a Brand Kit, Hub propagates the fields into the Brief; downstream business skills (`product-shots-main-image`, `product-shots-detail-page`, `product-shots-ad-creative`, `product-shots-social-post`) read those fields directly. When absent, defaults from the matched industry DNA fill in.