--- name: product-shots-social-post description: 'Designs social-platform-native visuals (Feed, Story, Reel, Carousel formats) for Instagram, TikTok, Facebook, Pinterest, RedNote, LinkedIn, X/Twitter and other social platforms — with platform-correct dimensions, safe zones, industry visual DNA, engagement hooks, and cross-slide consistency. Use when the user says "social post", "Instagram post", "IG post", "TikTok post", "Facebook post", "Pinterest pin", "social carousel", "feed post", "story post", "make a post", "design a social visual", "社媒帖", "做一个社媒图", or any underspecified social-media visual request. Routed from `product-shots` for the organic-social branch (non-ad).' license: MIT metadata: author: motiful source: product-shots ecosystem skill_id: product_shots_social_post version: "1.0" --- # Social Post Designs social-platform-native visuals (Feed, Story, Reel, Carousel) across Instagram, TikTok, Facebook, Pinterest, RedNote, LinkedIn, X/Twitter and other social platforms by combining nine canonical formats, seven industry visual-DNA presets, a seven-step workflow, a carousel framework with cross-slide consistency anchoring, and a self-audit gate. The skill produces a design description, optional caption, and self-check score per output. The format taxonomy (Feed Square 1:1 / Feed Portrait 4:5 / Story 9:16 / Reel Cover 9:16 / Carousel 4:5 / etc.) maps directly across Instagram, TikTok, Facebook, RedNote, and Pinterest — the same aspect ratios are platform-native on all of them. Platform-specific safe-zone tuning lives in `references/hard-constraints.md`. ## Engagement Principles These rules apply across every Section. Read before acting. 1. **Lock dimensions first** — every request resolves to one of nine formats with explicit width × height and aspect ratio. No format = no work. 2. **Industry DNA before composition** — match the user's industry to one of the seven presets; load its prompt patch + composition + color + lighting + common errors as a single bundle. 3. **Layered constraint priority** — Hard Constraints (Section 0) > Industry Rules (Section 1) > User Preferences > Model defaults. When user color overrides, industry default yields. 4. **Carousel consistency is per-slide repetition** — the consistency anchor is repeated verbatim at the start of every slide's prompt, not declared once. 5. **Mandatory self-audit before delivery** — every output passes the 14-item check (Section 4) and emits the seven-line Self-Check score. 6. **Banned words are filtered out of generator prompts** — platform names / UI terms / screenshot terms / brand-tool names never reach the image model. They are used only for internal format selection and industry matching. 7. **Match the user's language** — respond in English if user writes English, in Chinese if user writes Chinese. Never switch language unprompted. 8. **Use `` for option sets** — when proposing platform / format / industry choices, wrap them in `` tags. Never ask multiple questions at once. ## Execution Procedure ``` generate_social_visual(user_request) → design_description + caption + self_check # Step 0 — Pin hard constraints (MUST, before any decision) load references/hard-constraints.md → Dimensions table / Safe Zones / Text Overlay Rules / Design Quality Baseline / Banned Words keep these in working context for Steps 1, 5, 6 — violation produces fake UI artifacts, watermarks, occluded CTAs, or platform-policy breaks. # Step 1 — Confirm Format and Scenario (lock dimensions first) format = resolve_format(user_request) if user specified format → use it else apply default scenario logic: single image content → Feed Portrait 4:5 multi-page knowledge → Carousel 4:5 short-lived / ad → Story 9:16 short-video cover → Reel Cover 9:16 dimensions, ratio, safe_zone = lookup(format, references/hard-constraints.md §Dimensions + §Safe Zones) # Step 2 — Identify Industry (auto-load Visual DNA) industry = match_industry(user_request, candidates=[Beauty, Fashion, Tech, Lifestyle, Travel, Food, Fitness]) if matched → load references/industry-dna.md → bundle(prompt_patch, composition, color, lighting, common_errors) if no match → pick closest industry as base + adjust per user request # Step 3 — Define Engagement Goal goal = SHARE | SAVE | COMMENT if user specified → use it else infer from content type: education / how-to → SAVE lifestyle / humor → SHARE opinion / debate → COMMENT # Step 4 — Define the Hook (3-Second Rule) hook_type = Bold Claim | Curiosity Gap | Visual Shock drives Slide-1 design (Carousel) or headline strategy (single image) # Step 5 — Composition + Color (Industry × Format cross-decision) composition = industry.composition + format.safe_zone constraints color = brand_color (if exists, overrides) or industry.color lighting = industry.lighting text = format.text_overlay_rule (references/hard-constraints.md §Text Overlay) if format == Carousel: slides = build_carousel(content, hook_type, industry_bundle, brand_color, goal) # references/carousel-framework.md # Step 6 — Self-Check Gate (mandatory) audited_output = run_workflow(user_request) # references/workflow-and-self-check.md # runs Section 2 steps + Section 4 14-item audit # + re-validates against references/hard-constraints.md # (sizing, safe zone, overlay, quality, banned words) if any item fails → revise prompt, regenerate if all pass → emit self_check score block # Step 7 — Iterative Refinement on user satisfied → offer style variants / cross-platform adaptation / Carousel expansion / caption (if absent) on user request → adjust color / composition / style / format / hook (supports local edit, no full regen) # Output assembly grid_strategy, caption = finalize_grid_and_caption(format, user_caption, brand_account_context) # references/grid-and-caption.md emit design_description (6 items per references/workflow-and-self-check.md §Section 6) emit caption — separate text block, never rendered into image emit self_check_score (7-line block) ``` ## TOC of Module Files - `references/hard-constraints.md` — Section 0 (Dimensions / Safe Zones / Text Overlay / Quality Baseline) + Section 9 (Prompt Banned Words). MUST-level. Loaded at EP Step 0. - `references/industry-dna.md` — Section 1: seven industries × six dimensions (Prompt Patch, composition, color, lighting, common errors, social references). - `references/carousel-framework.md` — Section 3: 7-Slide Framework + Swipe Psychology + Visual Consistency and Typography (cross-slide anchor template). - `references/workflow-and-self-check.md` — Section 2 (Core Workflow seven steps) + Section 4 (Common Mistakes self-audit, 14 items) + Section 6 (Output Format). - `references/grid-and-caption.md` — Section 5 (Feed Grid Aesthetics, five strategies) + Section 7 (Caption & Copywriting incl. Social Caption Persona). ## Section Index ``` Goal Language Rule 0. Hard Constraints → references/hard-constraints.md Dimensions / Safe Zones / Text Overlay / Quality Baseline 1. Industry Visual DNA → references/industry-dna.md 1.1 Beauty / 1.2 Fashion / 1.3 Tech / 1.4 Lifestyle 1.5 Travel / 1.6 Food / 1.7 Fitness 2. Core Workflow → references/workflow-and-self-check.md §Workflow Step 1: Confirm Format and Scenario — Lock Dimensions First Step 2: Identify Industry — Auto-Load Visual DNA Step 3: Define Engagement Goal Step 4: Define the Hook — 3-Second Rule Step 5: Composition and Color — Industry × Format Cross-Decision Step 6: Self-Check Gate Step 7: Iterative Refinement 3. Carousel Standards (Applies when format = Carousel) → references/carousel-framework.md A. The 7-Slide Framework B. Swipe Psychology C. Visual Consistency and Typography 4. Common Mistakes and Self-Audit (Mandatory Gate) → references/workflow-and-self-check.md §Self-Audit 5. Feed Grid Aesthetics → references/grid-and-caption.md §Grid Common Grid Strategies / Grid Rules 6. Output Format → references/workflow-and-self-check.md §Output Format Design Description (6 Items) / Caption / Self-Check Score 7. Caption & Copywriting → references/grid-and-caption.md §Caption In-Image Text vs. Caption / Caption Logic / Social Caption Persona 8. Prompt Banned Words — Prevent Artifacts / Watermarks / Screenshot Look → references/hard-constraints.md §Section 9 IMPORTANT！Suggestion ``` ## Goal Design social-platform-native visuals (Feed, Story, Reel, Carousel) across Instagram, TikTok, Facebook, Pinterest, RedNote, LinkedIn, and X/Twitter — platform-correct (dimensions / safe zones), industry-appropriate (seven Visual DNA presets), engagement-tuned (SHARE / SAVE / COMMENT), and grid-coherent (Feed harmony). Every output passes a 14-item self-audit and emits a seven-line self-check score. ## Language Rule ``` Always respond in the user's language. IF user writes in English THEN respond in English IF user writes in Chinese THEN respond in Chinese NEVER switch language unprompted. ``` ## IMPORTANT — Suggestion Format ``` IMPORTANT！Suggestion: Always use format to guide the user. Do not ask several questions at once. Example: use format to provide options like Instagram / TikTok / Facebook / Pinterest / RedNote / LinkedIn / X (Twitter) / Other platform. ``` This is the front-end rendering instruction — option sets are wrapped in `` tags so the UI renders them as clickable chips. ## Cross-Skill Notes - **Upstream router**: `product-shots` routes here for the organic-social branch when `asset_type ∈ {post, carousel, feed, story, reel}` AND `is_promotion != True`. Promotional / ad creative requests route to `product-shots-ad-creative` instead. - **Industry Visual DNA presets** (seven industries) are shared with `product-shots` and `product-shots-ad-creative` (cross-skill consistency). - **Sibling skills**: `product-shots-main-image` / `product-shots-detail-page` (Amazon product/detail page imagery) — can produce source assets that get repurposed for social posts; `product-shots-multi-angle` (model 9-angle series) — produces fashion lookbook content that can be reframed for social Carousel. `product-shots-ad-creative` handles paid promotion / ad-objective creative with platform takedown-risk rules. - **Image generation backend**: rendered prompts are dispatched to `product-shots-image-gen` (the product-shots image-gen engine) which abstracts the underlying API (OmniMaaS / OpenAI / Gemini). ## Tooling The skill emits design prompts and self-check output. Image generation is invoked through `product-shots-image-gen` (the product-shots image-gen engine) using the prompts produced here.