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 leggiemint/legnext-skills --skill legnext-midjourneygit clone --depth 1 https://github.com/leggiemint/legnext-skillsWrote 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/leggiemint/legnext-skills/legnext-midjourney)<a href="https://agentmods.dev/skills/leggiemint/legnext-skills/legnext-midjourney"><img src="https://agentmods.dev/badge/skills/leggiemint/legnext-skills/legnext-midjourney/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/leggiemint/legnext-skills/legnext-midjourney"><img src="https://agentmods.dev/badge/skills/leggiemint/legnext-skills/legnext-midjourney.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 | $0.00062 | $0.02278 |
| Opus 5 | $0.00031 | $0.01139 |
| Sonnet 5 | $0.00012 | $0.00456 |
| Haiku 4.5 | $0.00006 | $0.00228 |
Grade A, and why
legnext-midjourney 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 12d 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Legnext Midjourney
Generate professional AI images using Midjourney's capabilities through the Legnext API.
Setup
CRITICAL: This skill requires a Legnext API key. Before running, check if the user has configured their API key:
Check for existing configuration:
- Look for a
.envfile in the project directory or parent directories - Check for
LEGNEXT_API_KEY=<key>in the.envfile - Or check environment variable:
echo $LEGNEXT_API_KEY
If not found, inform the user they need to:
Option 1: Create a .env file (recommended)
# Create .env file in the project root
echo "LEGNEXT_API_KEY=your-api-key-here" > .env
Option 2: Set environment variable
export LEGNEXT_API_KEY=your-api-key-here
Get an API key from:
https://legnext.ai/app/api-keys
Verify API key:
python scripts/verify_api_key.py
The scripts will automatically detect the .env file and provide clear error messages if the API key is missing or invalid.
Quick Start
For simple image generation requests:
python scripts/generate_and_wait.py "a beautiful sunset over mountains --v 7 --ar 16:9"
This handles the complete workflow: submit task → poll status → return results.
Complete Workflow
1. Understand the User's Request
Identify what type of image the user wants:
- Subject matter (people, landscapes, objects, abstract)
- Style (photographic, illustrated, artistic)
- Mood and atmosphere
- Technical requirements (aspect ratio, quality)
2. Craft the Prompt
Transform the user's natural language request into an effective Midjourney prompt.
Use the 7-Element Framework for systematic prompts:
- Subject, Medium, Environment, Lighting, Color, Mood, Composition
Quick structure:
[Subject] [Description] [Environment] [Lighting] [Style] [Parameters]
Example transformations:
User request: "I need a professional headshot"
→ Prompt: professional headshot, studio lighting, neutral background, sharp focus, 85mm lens --ar 2:3 --style raw
What ships with it
9 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.
- references/api_reference.md 6.7 KB
- references/midjourney_parameters.md 7.9 KB
- references/photography.md 7.9 KB
- references/prompt_engineering.md 9.8 KB
- requirements.txt 238 B
- scripts/generate_and_wait.py 5.4 KB runs code
- scripts/get_task.py 3.4 KB runs code
- scripts/imagine.py 3.5 KB runs code
- scripts/verify_api_key.py 2.5 KB runs code
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.
- 12d ago First seen · 302 lines · 62 tokens per session scan A ac2d305c230a
legnext-midjourney is a skill published in the GitHub repository leggiemint/legnext-skills (4 stars, last pushed 8mo ago), licensed MIT. It adds 62 tokens to every session and 2,278 once invoked, about $0.0003 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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