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 Modellix/modellix-plugin --skill modellix-image-prompt-engineeringgit clone --depth 1 https://github.com/Modellix/modellix-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/modellix/modellix-plugin/modellix-image-prompt-engineering)<a href="https://agentmods.dev/skills/modellix/modellix-plugin/modellix-image-prompt-engineering"><img src="https://agentmods.dev/badge/skills/modellix/modellix-plugin/modellix-image-prompt-engineering/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/modellix/modellix-plugin/modellix-image-prompt-engineering"><img src="https://agentmods.dev/badge/skills/modellix/modellix-plugin/modellix-image-prompt-engineering.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 | $0.00133 | $0.02444 |
| Opus 5.5 | $0.00053 | $0.00978 |
| Sonnet 5.5 | $0.00027 | $0.00489 |
| Haiku 4.5 | $0.00013 | $0.00244 |
Grade A, and why
modellix-image-prompt-engineering 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 1mo 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Modellix Image Prompt Engineering
Convert an image idea into a deliberate, execution-ready prompt. This skill is the
creative planning layer; modellix-design is the execution layer.
Do not submit, poll, download, authenticate, or inspect model schemas here. Do not
run the Modellix CLI. When the user wants an image generated, finish the brief
first and then hand it to modellix-design.
Route the request
Use this skill when any of these are true:
- The request is a vague visual brief: "make it premium," "create a launch cover," or "give me a clean product graphic."
- The user wants a prompt written, expanded, repaired, or made less generic.
- The task needs art direction, composition, on-image text, a reference strategy, or a coherent batch/grid.
- An earlier result failed visually and the prompt needs a targeted revision.
Skip or keep the pass minimal when:
- The user supplied a complete prompt and explicitly asked only to run it. Pass it
directly to
modellix-design. - The request is about video, audio, credentials, task status, downloads, model
schemas, or command syntax. Use
modellix-design. - The user only wants image compression, format conversion, cropping, or reuse of an existing asset without generative changes.
If a supplied prompt is already specific, perform at most a one-line readiness check. Do not rewrite it merely to demonstrate this skill.
Core principle: maximize decision density
Prompt quality is not proportional to prompt length. A strong prompt packs useful visual decisions into each phrase.
Before writing, fill three slots:
- Subject — the actual person, object, product, scene, or information.
- Visual system — an established design movement, studio, brand language, medium tradition, or precisely described visual grammar.
- Medium — poster, instruction manual, editorial illustration, packaging, product photograph, infographic, UI screen, icon sheet, and so on.
Prefer precise, recognizable references over adjective piles:
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 280 lines · 133 tokens per session scan A 764dde5de746
modellix-image-prompt-engineering is a skill published in the GitHub repository Modellix/modellix-plugin (1 stars, last pushed 2d ago), licensed MIT. It adds 133 tokens to every session and 2,444 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-16.
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