---
name: anycap-social-meme-workflows
description: "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."
metadata:
  version: 0.6.4
  website: https://anycap.ai
license: MIT
compatibility: Requires anycap CLI binary and internet access. Works with agents that can run shell commands and create local files.
---

# 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 <model-id> schema --operation generate --mode <mode>
```

### 3. Generate or edit the base visual

Text-to-image example:

```bash
anycap image generate \
  --model <model-id> \
  --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 <model-id> \
  --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 <model-id> \
  --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.