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 xinvxueyuan/NovelAI-Image-MCP --skill novelai-workflowsgit clone --depth 1 https://github.com/xinvxueyuan/NovelAI-Image-MCPWrote 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/xinvxueyuan/novelai-image-mcp/novelai-workflows)<a href="https://agentmods.dev/skills/xinvxueyuan/novelai-image-mcp/novelai-workflows"><img src="https://agentmods.dev/badge/skills/xinvxueyuan/novelai-image-mcp/novelai-workflows/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/xinvxueyuan/novelai-image-mcp/novelai-workflows"><img src="https://agentmods.dev/badge/skills/xinvxueyuan/novelai-image-mcp/novelai-workflows.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 | $0.00045 | $0.04199 |
| Opus 5 | $0.00023 | $0.02099 |
| Sonnet 5 | $0.00009 | $0.00840 |
| Haiku 4.5 | $0.00005 | $0.00420 |
Grade A, and why
novelai-workflows 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 — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
novelai-workflows
Instructions for the agent to follow when chaining NovelAI tools into multi-step creative pipelines.
When to use
Use this skill when the user asks for a multi-step image pipeline or workflow recipe — e.g. generate then upscale for higher resolution, build a ControlNet-style pipeline (txt2img → annotate → img2img), apply Director edits to an existing image (img2img → director), or run a full end-to-end production flow (txt2img → director → upscale). It covers how to wire the 11 NovelAI MCP tools and the matching CLI commands into chains. For individual tool parameters, see the novelai-mcp-tools skill; for CLI flags, see the novelai-cli skill — do not duplicate those references here.
Instructions
Prerequisites
- Credentials configured:
NOVELAI_TOKEN(preferred) orNOVELAI_USERNAME+NOVELAI_PASSWORD. - Output directory writable:
NOVELAI_OUTPUT_DIR(defaultoutputs), or pass-o <dir>per CLI invocation. - MCP: a connected MCP host (Claude Desktop, Cline, or
mcp dev apps/server/dev_server.py). CLI:novelai-image-mcponPATH(oruvx novelai-image-mcp, oruv run --directory apps/server novelai-image-mcp). - Check Anlas balance before expensive chains — call
get_subscription(MCP) ornovelai-image-mcp info(CLI) first. Upscale and Director tools cost Anlas proportional to source resolution.
-
txt2img → upscale — generate then upscale for higher resolution.
Goal: generate an image, then upscale it for higher resolution than the generator produces natively.
When to use: you need a final image larger than the model's native output, or you want to refine detail on a low-step draft before committing Anlas to a full-resolution render.
MCP sequence:
generate_image(prompt="...", width=832, height=1216, seed=42)→ returnsImageContent+ path likeoutputs/generate-<ts>.png.- Read that PNG, base64-encode it, and call
upscale_image(image="<base64>", factor=4)→ returns the 4× PNG (outputs/upscale-<ts>.png).
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 · 336 lines · 45 tokens per session scan A ca91883cb046
novelai-workflows is a skill published in the GitHub repository xinvxueyuan/NovelAI-Image-MCP (4 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 4,199 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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