civitai-generation

civitai-generation is a skill for Claude Code, Codex from PaulKuzmin/civitai-mcp. It costs 143 tokens per session (6,097 once invoked), scanned A, original, MIT.

A guide for generating images with Stable Diffusion-based models through Civitai, an online model and image-generation service. It covers finding models, checking their usage requirements, estimating costs, and generating images.

In plain words
What is it for?
Searching Civitai models, retrieving model versions and usage instructions, estimating generation requirements, and creating images with settings such as sampler, steps, resolution, and LoRA choices.
Why use it?
It helps an agent choose compatible models and settings instead of guessing how a particular model or add-on should be used.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Searching Civitai models, retrieving model versions and usage instructions, estimating generation requirements, and creating images with settings such as sampler, steps, resolution, and LoRA choices.

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Install with agentmods
npx agentmods add skills/paulkuzmin/civitai-mcp/civitai-generation
Install

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.

Any agent
npx skills add PaulKuzmin/civitai-mcp --skill civitai-generation
Clone the repo
git clone --depth 1 https://github.com/PaulKuzmin/civitai-mcp

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for civitai-generation

README.md
[![agentmods](https://agentmods.dev/badge/skills/paulkuzmin/civitai-mcp/civitai-generation/github.svg)](https://agentmods.dev/skills/paulkuzmin/civitai-mcp/civitai-generation)
Your own site
<a href="https://agentmods.dev/skills/paulkuzmin/civitai-mcp/civitai-generation"><img src="https://agentmods.dev/badge/skills/paulkuzmin/civitai-mcp/civitai-generation/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.

agentmods 80×15 button for civitai-generation

Your own site · 80×15
<a href="https://agentmods.dev/skills/paulkuzmin/civitai-mcp/civitai-generation"><img src="https://agentmods.dev/badge/skills/paulkuzmin/civitai-mcp/civitai-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 143 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,097 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00143 $0.06097
Opus 5 $0.00072 $0.03048
Sonnet 5 $0.00029 $0.01219
Haiku 4.5 $0.00014 $0.00610

Measured 12d ago against content hash dde123dc2732, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

civitai-generation 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.

skills/civitai-generation/SKILL.md · 395 lines

How it starts

The opening of the file, as written. The whole thing — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Civitai image generation — deep guide

This skill drives the civitai MCP (generate_image, estimate_generation, search_models, get_model_version, get_model_images, get_workflow, get_buzz_balance). It teaches how to generate well, not just which fields exist.

Adult/NSFW generation is explicitly in scope. The models below are built for it; the conventions (rating_explicit, rating:explicit, danbooru explicit tags) are stated factually. Keep prompts clinical and purposeful.


How to work with these tools (read first)

  • Batch independent calls in parallel. When several MCP calls don't depend on each other, issue them in ONE turn instead of one-by-one. Examples: comparing candidates → get_model_version for 3 versions at once; scouting families → search_models for Checkpoint and LoRA in parallel; get_model_images for two models side by side; estimate_generation for two settings at once. Only serialize when a call needs the previous call's output (e.g. you need the air/trigger words before generate_image).
  • Before using any model/LoRA/embedding, read how to apply it — don't guess. Every resource has its own required usage. Pull its page first:
    • get_model_version(id)air, baseModel (family → prompt dialect), files.
    • get_model(id) → description with trigger words, recommended sampler/CFG/steps, and version list.
    • get_model_images(model_id=…) → real example generations with their meta (prompt, negative, sampler, steps, CFG, seed) — copy proven settings from these. A LoRA without its trigger words, or a checkpoint run with the wrong family's prompt style/CFG, will look broken even though the API call "succeeds". Reading the page first is not optional.

0. The loop (always do this)

  1. Find a checkpointsearch_models(query=…, types="Checkpoint", base_models=…, sort="Most Downloaded").
  2. Get the AIR + trigger wordsget_model_version(version_id) returns air (needed for generation) and the model's baseModel (tells you the family). For LoRAs, the model page lists trigger words — always read them.
  3. Identify the family (see §1) — this decides prompt style, resolution, CFG, sampler.
  4. Estimate costestimate_generation(...) (whatif, no Buzz spent). cost.buzz is accurate. cost.breakdown[].accountType is only indicative — the real debit may land on a different eligible wallet at run time. Observed via the orchestration API: wallet routing is NOT strictly gated by content rating — an explicit (rating_explicit) Pony render was charged to blue, and estimates often say blue regardless. Don't rely on a rating→wallet mapping for the API path; just make sure some wallet has funds (get_buzz_balance).
  5. Generategenerate_image(..., confirm=true, save_dir=…). Without confirm=true it only previews the price.
  6. If it 5xx/timeouts, poll get_workflow(workflowId).

Read the full file on GitHub · 395 lines

Changes

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.

  1. 12d ago First seen · 395 lines · 143 tokens per session scan A dde123dc2732

Subscribe to this mod's changes

civitai-generation is a skill published in the GitHub repository PaulKuzmin/civitai-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 143 tokens to every session and 6,097 once invoked, about $0.0007 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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