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 skills add danielrosehill/Claude-Visual-Communications-Plugin --skill generate-visual-promptgit clone --depth 1 https://github.com/danielrosehill/Claude-Visual-Communications-PluginWrote 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/skills/danielrosehill/claude-visual-communications-plugin/generate-visual-prompt)<a href="https://agentmods.dev/skills/danielrosehill/claude-visual-communications-plugin/generate-visual-prompt"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-visual-communications-plugin/generate-visual-prompt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/danielrosehill/claude-visual-communications-plugin/generate-visual-prompt"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-visual-communications-plugin/generate-visual-prompt.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00033 | $0.00913 |
| Opus 5 | $0.00016 | $0.00456 |
| Sonnet 5 | $0.00007 | $0.00183 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
generate-visual-prompt scanned grade A with 0 findings 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Visual Prompt
Transform a visual concept into a detailed, model-optimized prompt for image or video generation with 2–3 variations and model-specific guidance.
When to use
- User has selected a visual from ideation and wants a generation prompt
- User wants to refine a prompt for a specific generation model (Flux, SDXL, video)
- User wants multiple prompt variations to explore different interpretations
Inputs to gather
- Visual concept — Description of the visual to create (or reference to ideation.md)
- Project context — Project name (if not active) and any style/brand constraints from project.yaml
- Preferred model — Flux | SDXL | video | user preference
- Technical specs — Desired resolution, aspect ratio, format
- Iteration constraints — Any elements to emphasize or avoid
Procedure
-
Load project context. Check for an active project; if not, ask the user to specify. Read
project.yamlfor style preferences, target platform, and resolution guidelines. -
Clarify the visual concept. If the user references an idea from
ideation.md, read that file. If providing a new concept, confirm the visual type, mood, and purpose. -
Determine generation method. Identify whether this is text-to-image, image-to-image, or video generation based on the concept and user intent.
-
Structure the prompt. Use this framework: [Subject] + [Style] + [Composition] + [Lighting/Mood] + [Technical Specs]
- Subject — Main focus, key elements, actions or states
- Style — Artistic style (photorealistic, illustration, 3D render, etc.); color palette; reference artists if appropriate
- Composition — Framing (close-up, wide, etc.); perspective; layout and focal points
- Lighting/Mood — Lighting type; atmosphere; emotional tone
- Technical — Aspect ratio, resolution, any platform-specific needs
-
Generate 2–3 prompt variations. Create variations that:
- Explore different style approaches or moods
- Vary composition or emphasis
- Test model-specific keyword strategies
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.
- 8d ago First seen · 88 lines · 33 tokens per session scan A 9ad92f099944
generate-visual-prompt is a skill published in the GitHub repository danielrosehill/Claude-Visual-Communications-Plugin (2 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 913 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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