image-generation

image-generation is a skill for Claude Code, Codex from shinpr/mcp-image. It costs 43 tokens per session (1,212 once invoked), scanned A, original, MIT.

A guide for improving prompts used to create or edit images. It organizes details about the subject, setting, and visual style.

In plain words
What is it for?
Use it to write prompts for illustrations, photos, visual assets, and image edits across image-generation tools.
Why use it?
It helps turn vague image requests into clearer descriptions while preserving the user's intended details.

Skill for Claude CodeCodex

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

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.

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

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 image-generation

README.md
[![agentmods](https://agentmods.dev/badge/skills/shinpr/mcp-image/image-generation.svg)](https://agentmods.dev/skills/shinpr/mcp-image/image-generation)
Your own site
<a href="https://agentmods.dev/skills/shinpr/mcp-image/image-generation"><img src="https://agentmods.dev/badge/skills/shinpr/mcp-image/image-generation.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,212 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00043 $0.01212
Opus 5 $0.00022 $0.00606
Sonnet 5 $0.00009 $0.00242
Haiku 4.5 $0.00004 $0.00121

Measured 6d ago against content hash 43acbbc62107, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

image-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 6d 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/image-generation/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Image Generation Prompt Best Practices

Prompt Structure

Enhance every image generation prompt around three core elements:

1. SUBJECT (What)

  • Physical characteristics: textures, materials, colors, scale
  • Actions, poses, expressions if applicable
  • Distinctive features that define the subject

2. CONTEXT (Where/When)

  • Setting, background, spatial relationships (foreground, midground, background)
  • Time of day, weather, atmospheric conditions
  • Mood and emotional tone of the scene

3. STYLE (How)

  • Artistic or photographic approach: reference specific artists, movements, or styles
  • Camera/lens choices: specify focal length, aperture, and shooting angle when photographic

Core Principles

  • Preserve intent — Add visual details (lighting, texture, composition) only in areas the user left unspecified; keep all user-specified elements unchanged
  • Positive descriptions only — Describe what should be present; rephrase any exclusion as an inclusion
  • Specific over vague — "golden hour sunlight at 15° angle" beats "nice lighting"
  • Natural flow — Weave elements into a single flowing description, not a bullet list

Output Format

Return the enhanced prompt as a single flowing paragraph. When the user provides multiple requests, return each as a separate enhanced prompt under a labeled heading.

Enhancement Patterns

Hyper-Specific Details

Add concrete visual details for any Subject/Context/Style element not specified by the user:

  • Lighting → direction, quality, color temperature, shadow behavior
  • Textures → surface materials, weathering, reflectivity
  • Atmosphere → particulates, humidity, depth haze
  • Scale → relative sizes, distances, proportions

Camera Control Terminology

When a photographic look is appropriate:

  • Lens type: "shot with 85mm portrait lens", "wide-angle 24mm"
  • Aperture: "shallow depth of field at f/1.8", "deep focus at f/11"
  • Angle: "low angle emphasizing height", "bird's eye view"
  • Motion: "motion blur on the paws", "frozen mid-action"

Read the full file on GitHub · 138 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. 6d ago First seen · 138 lines · 43 tokens per session scan A 43acbbc62107

Subscribe to this mod's changes

image-generation is a skill published in the GitHub repository shinpr/mcp-image (157 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 1,212 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 2026-08-30.

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