Install
$ agentstack add skill-j1ngg-tech-marketing-framework-image ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Marketing Image Generator
This skill generates images for marketing assets using the mcp__mcp-image__generate_image MCP tool. It reads brand guidelines to maintain visual consistency and constructs optimized prompts for each use case.
Prerequisites
Required: The mcp-image MCP server must be configured and running.
Step 1: Check Brand Guidelines
Before generating any images, read docs/inputs/brand_guidelines.md.
If it exists and is filled in: Extract visual style, color palette, mood, motifs, composition preferences, and restrictions. Use these to constrain every prompt.
If it exists but is still a template (placeholder values): Tell the user:
> "Your brand guidelines at docs/inputs/brand_guidelines.md are still the default template. I can generate images without them, but results will be generic. Would you like to fill in the guidelines first?"
If the user wants to proceed without guidelines, use sensible defaults: clean, minimal, professional, tech-focused.
Step 2: Gather Inputs
Ask the user:
- What is this image for?
- Social media post (LinkedIn, Twitter)
- Blog featured image
- Ad creative
- Presentation slide
- Other (describe)
- Source content — What should the image represent?
- File path to the content it accompanies
- Description of the concept
- Or let the skill extract the concept from context (if already in a content generation flow)
- Reference image — (Optional) Do you have a reference image for style matching?
- If yes, provide the absolute file path
Wait for answers before proceeding.
Step 3: Select Format
Based on the use case, select the appropriate aspect ratio and resolution:
| Use Case | Aspect Ratio | Resolution | Notes | |----------|-------------|------------|-------| | LinkedIn post | 16:9 | 2K | Horizontal, feed-optimized | | Twitter post | 16:9 | 2K | Horizontal, timeline-optimized | | Blog featured image | 16:9 | 2K | Standard blog header | | LinkedIn ad | 1:1 | 2K | Square format for sponsored content | | Meta ad | 4:5 | 2K | Vertical, mobile feed-optimized | | Presentation slide | 16:9 | 2K | Horizontal, projector-friendly | | Instagram post | 1:1 | 2K | Square format |
Confirm the format with the user before generating. If the user requests a custom aspect ratio, use the closest supported option from the tool (1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9).
Step 4: Construct the Prompt
Build the prompt in three layers:
Layer 1: Style (from brand guidelines)
Extract from docs/inputs/brand_guidelines.md:
- Visual style (e.g., "minimalist tech illustration")
- Color palette (e.g., "dark navy background, electric blue and white accents")
- Mood (e.g., "professional, innovative, bold")
- Visual motifs (e.g., "geometric shapes, abstract connections")
Layer 2: Concept (from source content)
Derive the visual concept from the source content. Rules:
- Abstract over literal. Represent the concept, not a screenshot of the product.
- One focal point. Do not try to illustrate every idea in the content.
- Pick the single most visually interesting element from the source.
Layer 3: Restrictions (fixed + brand guidelines)
Always include:
- "No text, no words, no letters, no labels, no typography"
- "No photorealistic human faces"
- "Clean composition with clear focal point"
- Any brand-specific restrictions from guidelines
Prompt Template
[Style: visual style, color palette, mood from brand guidelines]
[Concept: single visual idea derived from source content]
[Composition: layout guidance based on use case]
No text, no words, no letters, no labels, no typography. No photorealistic human faces. Clean composition with clear focal point. [Additional brand restrictions]
Prompt rules:
- Keep prompts under 200 words. Shorter prompts produce more coherent images.
- Use concrete visual descriptions, not abstract marketing language.
- Specify colors by name and relationship ("dark navy background with electric blue accent lines"), not hex codes.
- Describe spatial relationships ("left side", "center", "flowing from left to right").
- Include lighting direction if relevant ("backlit", "soft ambient glow").
Step 5: Generate
Call the MCP tool with the constructed parameters:
mcp__mcp-image__generate_image(
prompt: [constructed prompt],
aspectRatio: [from format table],
imageSize: [from format table],
purpose: [use case description],
quality: "quality",
fileName: [descriptive file name]
)
File naming: [context]-[concept]-[use-case] (e.g., beyond-identity-agent-governance-linkedin, ceros-credential-flow-blog-header)
If a reference image was provided: Include inputImagePath with the absolute path.
After generation, read the output image and present it to the user.
Step 6: Review and Refine
After presenting the image, ask:
> "Want to iterate on this, or is it good?"
Refinement
If the user wants changes, adjust the prompt based on their feedback. Common adjustments:
| Feedback | Prompt Adjustment | |----------|-------------------| | "Too busy / complicated" | Reduce elements, add "minimal, sparse, lots of negative space" | | "Too dark" | Shift to "light background, bright, well-lit" | | "Too generic" | Add more specific visual motifs from the source content | | "Wrong colors" | Explicitly name the desired colors | | "Too many words/labels" | Strengthen the no-text restriction: "absolutely no text, no labels, no annotations, no typography of any kind" | | "Not abstract enough" | Remove concrete objects, add "abstract, geometric, flowing shapes" |
Maximum 5 refinement rounds. After 5 attempts:
> "We've done 5 rounds. To get closer to what you want, I'd recommend:" > > 1. Providing a reference image that captures the style you're after > 2. Updating brand guidelines with more specific visual direction > 3. Trying a completely different visual concept
Output
Images are saved to output/images/ automatically by the MCP tool.
After the image is approved, provide:
Image: output/images/[filename].jpg
Dimensions: [aspect ratio] at [resolution]
Prompt: [the prompt used, for future reference]
Alt text: [SEO-friendly description, under 125 characters]
Alt Text Rules
- Describe what is visually in the image, not the topic of the content
- 125 characters or fewer
- No "image of" or "picture of" prefix
- Include key visual elements and colors
Multi-Image Generation
When generating images for a set of assets (e.g., a blog post + social posts promoting it), maintain visual consistency:
- Use the same style layer across all prompts
- Vary the concept layer to match each asset's focus
- Keep the color palette consistent
- Adjust only the aspect ratio and composition per format
Adaptation Notes
- When brand guidelines are sparse: Default to clean, minimal, dark backgrounds with blue/white accents. Flag that results will improve with specific guidelines.
- When source content is highly technical: Focus on abstract representations. Do not try to literally illustrate architecture diagrams or code flows.
- When the tool generates text despite instructions: This is a known limitation of image generation models. Strengthen the no-text restriction and simplify the prompt. If text persists, note that the user can crop or overlay in post-production.
- When used alongside other skills: If called after
/social-posts,/blog, or/ads, extract the concept directly from the generated content without re-asking the user.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: j1ngg
- Source: j1ngg/tech-marketing-framework
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.