Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/dojocodinglabs/remotion-superpowers/generate-imagegit clone --depth 1 https://github.com/DojoCodingLabs/remotion-superpowersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/dojocodinglabs/remotion-superpowers/generate-image)<a href="https://agentmods.dev/commands/dojocodinglabs/remotion-superpowers/generate-image"><img src="https://agentmods.dev/badge/commands/dojocodinglabs/remotion-superpowers/generate-image.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00039 | $0.00833 |
| Opus 5 | $0.00019 | $0.00417 |
| Sonnet 5 | $0.00008 | $0.00167 |
| Haiku 4.5 | $0.00004 | $0.00083 |
Grade A, and why
generate-image scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -o public/images/[descriptive-name].png "[replicate_output_url]" How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Image — AI Image Creation
You are helping the user generate custom images for their Remotion video project.
Workflow
1. Understand the Need
Ask the user (if not already clear):
- What is the image for? — Scene background, thumbnail, character, product shot, abstract art, diagram?
- Style — Photorealistic, illustration, 3D render, flat design, watercolor, pixel art?
- Dimensions — Landscape (1920x1080), portrait (1080x1920), square (1080x1080)?
- Mood/Colors — Bright, dark, warm, cool, neon, pastel?
2. Craft the Prompt
Write a detailed image generation prompt. Good prompts include:
- Subject description
- Art style
- Lighting and mood
- Camera angle/perspective
- Color palette
- Background details
Good prompt examples:
- "Modern tech startup office, aerial view, clean minimalist design, bright natural lighting, white and blue color scheme, photorealistic"
- "Abstract geometric pattern, dark background, glowing neon purple and blue lines, futuristic, 3D render"
- "Friendly robot mascot waving, cartoon illustration style, pastel colors, clean white background, suitable for logo"
- "Golden hour cityscape, drone aerial shot, warm orange and pink sky, downtown skyline silhouette, cinematic"
3. Generate via remotion-media
Use remotion-media generate_image:
- prompt: [crafted prompt]
- project_path: [project root path]
The image is saved to the project's public/ directory.
4. Generate via Replicate MCP (if available)
If the user has REPLICATE_API_TOKEN set and wants more model options, use the Replicate MCP tools:
# FLUX for high-quality images
replicate_run:
model: "black-forest-labs/flux-1.1-pro"
input:
prompt: "[crafted prompt]"
aspect_ratio: "16:9"
output_format: "png"
Download the output to the project:
curl -o public/images/[descriptive-name].png "[replicate_output_url]"
Available Replicate models:
- FLUX 1.1 Pro (
black-forest-labs/flux-1.1-pro) — High quality, great prompt following - Imagen 4 (
google/imagen-4) — Google's latest, photorealistic - Ideogram v3 (
ideogram-ai/ideogram-v3) — Best for text-in-image - FLUX Kontext (
black-forest-labs/flux-kontext-pro) — Style control, multi-reference
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 100 lines · 39 tokens per session scan A 1a338fd8002b
generate-image is a command published in the GitHub repository DojoCodingLabs/remotion-superpowers (116 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 833 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
generate-all
Generate creative assets for all posts in the current month's calendar.
cost-report
Show API cost breakdown for the current month's production.
brand-setup
Configure a new brand profile with colors, fonts, logo, visual style, platforms, and compliance rules.
edit-image
Edit a generated image — adjust background, lighting, colors, or composition.
index-assets
Index or re-index a brand's visual asset library.
status
Show current production status for the active brand and month.