# Anycap Social Meme Workflows > Create meme-style images, funny meme drawings, captioned photos, and lightweight social visuals with AnyCap. Use when an agent needs to turn a joke, reaction, campaign hook, quote, or screenshot into a meme image, funny doodle-style meme drawing, captioned image, or short meme-video concept. Combines AnyCap image generation and editing with deterministic local text overlay, optional video generation, and Drive or Page delivery. - Skill: `anycap-ai/anycap-social-meme-workflows` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add anycap-ai/anycap-social-meme-workflows` - Raw SKILL.md: https://api.skillmd.com/api/skills/anycap-ai/anycap-social-meme-workflows/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - License: MIT - Author: anycap-ai (https://skillmd.com/u/anycap-ai) - Updated: 2026-09-10 - Page: https://skillmd.com/skills/anycap-ai/anycap-social-meme-workflows --- # AnyCap Social Meme Workflows Use this skill when the output needs to feel like a meme, captioned social post, or reaction visual, but still has to be reproducible. **Do not rely on image generation alone for exact caption text.** Use AnyCap to create or edit the base visual, then render the final caption locally so the text is exact. ## Read First Read these files before acting: 1. This file for the workflow 2. [references/workflows.md](references/workflows.md) for pattern selection, prompt formulas, and article mapping For detailed CLI syntax, authentication, and capability reference, use the `anycap-cli` skill. ## Best Fit Use this skill for: - meme-style hero images with exact top or bottom text - funny meme drawings with doodle-style internet humor - captioned photos for blog posts or social posts - reaction visuals from an existing screenshot or photo - short meme-video concepts where the still or base frame comes first - use-case demos that need both generated media and a repeatable workflow Do not use this skill for: - large meme-template databases - highly specific internet meme lore pages - exact brand or copyrighted character recreation requests - production subtitle pipelines with timing-heavy caption editing ## Core Rule Split the task into two layers: 1. **Base visual layer** with AnyCap 2. **Exact text layer** with deterministic local rendering Why: - image models are good at style, composition, and fast variation - image models are not dependable for long exact caption text - deterministic overlay keeps the final meme readable and repeatable ## Workflow ```mermaid graph LR A[Classify request] --> B[Choose model] B --> C[Generate or edit base visual with AnyCap] C --> D[Overlay exact text locally] D --> E[QA readability and punchline] E --> F[Deliver locally, via Drive, or via Page] ``` ### 1. Classify the request Choose one workflow first: - **Text-first meme**: the joke or caption exists; the visual supports it - **Funny meme drawing**: the humor mostly lives in the drawing style, pose, or absurd scene - **Reaction remix**: user supplies an image and wants meme treatment - **Captioned photo**: exact line of text on top of an image - **Meme-video concept**: still image, caption, then optional short video For funny meme drawings, default to one of these repeatable presets: - **Classic doodle**: the strongest default for blob characters, stick-figure-adjacent humor, and easy-to-draw meme pages - **Bad drawing**: useful when the joke works because the art is awkward or deliberately clumsy - **Rage-comic-adjacent**: only when you want old-web comic energy without relying on canonical rage faces or meme-lore cloning ### 2. Choose the model Choose from the live model catalog instead of relying on a hard-coded model list. Match the model to the job: - stronger first-pass visuals - editing an existing image or screenshot - fast variant generation, especially for funny meme drawings Always inspect the model list and schema before generating: ```bash anycap image models anycap image models schema --operation generate --mode ``` ### 3. Generate or edit the base visual Text-to-image example: ```bash anycap image generate \ --model \ --prompt "reaction-image style visual, exaggerated expression, blank top and bottom safe space for meme caption, high contrast, clean composition" \ --param aspect_ratio=1:1 \ --param resolution=2k \ -o meme-base.png ``` Image-to-image example: ```bash anycap image generate \ --model \ --mode image-to-image \ --prompt "turn this into a sharper reaction meme image, preserve the subject, simplify background, leave clear safe space for top and bottom caption" \ --param images=./source.png \ --param aspect_ratio=1:1 \ --param resolution=2k \ -o meme-remix-base.png ``` Prompt for negative space explicitly. Ask for "blank caption-safe area", "clean top band", or "empty bottom margin" instead of asking the model to write the exact meme text. Funny meme drawings example: ```bash anycap image generate \ --model \ --prompt "funny meme drawing, crude but charming internet doodle style, exhausted office goblin melting into an office chair while holding a tiny coffee cup, absurd tiny-problem energy, wildly exaggerated defeated expression, messy desk chaos without readable screens, thick sketch lines, off-white paper texture, muted green accents, obvious blank space for optional caption, no words, no letters, no watermark" \ --param aspect_ratio=4:3 \ --param resolution=2k \ -o funny-meme-drawing.png ``` For funny meme drawings, the caption is optional. If the humor already lands through the drawing alone, you can deliver the image as-is. If the joke needs exact wording, add the caption locally afterward. ### 4. Overlay exact text locally Preferred order: 1. existing local image toolchain already used by the repo or operator 2. simple SVG or HTML/CSS card rendered locally 3. ImageMagick if installed If no local renderer is available, create a simple SVG with: - bold uppercase title text - stroke or shadow for contrast - controlled padding and line breaks ### 5. QA the output Check: - exact caption text matches the requested copy - line breaks read well on mobile - subject and caption do not compete visually - punchline is legible in a thumbnail - the output still looks intentional without knowing the prompt If needed, use AnyCap image reading to inspect the result: ```bash anycap actions image-read \ --file ./final-meme.png \ --instruction "Read the visible text and describe whether the caption is easy to read at small size." ``` ### 6. Deliver - return the local file path when the human is in the same workspace - upload to Drive when they need a share link - publish a simple Page when the deliverable is a gallery or mini use-case report ## Use-Case Article Angle This skill supports workflow-led articles better than template-library articles. Good article angles: - how to make memes online with an AI agent - funny meme drawings with an AI agent - easy memes to draw with an AI agent - how to add text to a photo with an AI agent - how to make a meme video with an AI agent - how to create memes on Instagram without switching tools Bad article angles: - obscure meme-name pages - "blank template" databases - trend-chasing pages that need constant pop-culture maintenance ## Output Expectations A good run should usually produce: - 1 to 4 base visual variants - 1 exact-text final image - optional share link or published page - a short note explaining model choice and workflow ## Guardrails - Avoid copyrighted characters or branded logos unless the user provides a clear right to use them. - Do not promise exact text rendering from the model itself. - Prefer exact text overlay locally when the copy matters. - Avoid adult or hateful meme requests. - Treat meme style as a delivery format, not an excuse for sloppy output.