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 shaharsha/claude-skills --skill image-generationgit clone --depth 1 https://github.com/shaharsha/claude-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/shaharsha/claude-skills/image-generation)<a href="https://agentmods.dev/skills/shaharsha/claude-skills/image-generation"><img src="https://agentmods.dev/badge/skills/shaharsha/claude-skills/image-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.
<a href="https://agentmods.dev/skills/shaharsha/claude-skills/image-generation"><img src="https://agentmods.dev/badge/skills/shaharsha/claude-skills/image-generation.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 | $0.00173 | $0.03403 |
| Opus 5.5 | $0.00069 | $0.01361 |
| Sonnet 5.5 | $0.00035 | $0.00681 |
| Haiku 4.5 | $0.00017 | $0.00340 |
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 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generation
Two model families, three jobs.
Models covered
| Model ID | Family | Use for | Cost (1024×1536, measured 2026-10-02) |
|---|---|---|---|
gpt-image-2.5-sunburst |
OpenAI (Images 2.5, 2026-09-08) | Default. Anything that may ship. #1 on every major leaderboard (generation, editing, text rendering, portraits) | max ≈ $0.165, ~90 s · high ≈ $0.041, ~35 s |
gpt-image-2.5-flare |
OpenAI (Images 2.5) | Quick drafts — exploring directions, testing a prompt. Same prompts as Sunburst, ~2× faster | medium ≈ $0.01, ~15 s |
gemini-3-pro-image |
Google (Nano Banana Pro) | Close-up natural skin/hair when votes and reviewers disagree; up to 14 references | $0.134 (1K/2K) · $0.24 (4K) |
gemini-3.1-flash-image |
Google (Nano Banana 2) | Extreme aspect ratios (1:4…8:1), image-search grounding | $0.067 (1K) |
gemini-3.1-flash-lite-image |
Google (Nano Banana 2 Lite) | Cheapest Gemini exploration; 1K only, returns JPEG | $0.034 |
gpt-image-2 still works (not deprecated) but is a step below both 2.5 models. The Gemini *-preview IDs and all Imagen models are shut down — the scripts refuse them.
The three jobs of this skill
- Pick the model and the quality for the asset. See reference/model-selection.md.
- Write the prompt following the model's house rules. The two providers want opposite things:
- OpenAI GPT Image 2.5 wants labeled sections (scene / subject / details / constraints), exact text in quotes, and accepts inline exclusions ("no extra text, no watermarks"). Read reference/openai-gpt-image.md.
- Gemini wants narrative paragraphs, negative phrasing backfires (rewrite "no people" as "empty street"), aspect ratio goes in
imageConfig. Read reference/gemini-image.md.
- Run the API via the bundled scripts. See scripts/README.md.
Quality on 2.5 — the trap
The 2.5 quality ladder was re-cut. At the same size, 2.5 high buys about the output tokens of gpt-image-2 medium; 2.5 max buys what gpt-image-2 high did (measured: Sunburst 1024×1536 high = 1,372 output tokens, max = 5,488). Copying "quality=high" from old habits silently ships a medium-detail image.
What ships with it
24 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.
- .gitignore 30 B
- examples.md 17 KB
- README.md 9.7 KB
- reference/characters-from-photos.md 8.6 KB
- reference/gemini-image.md 18 KB
- reference/hebrew-rtl.md 8.4 KB
- reference/model-selection.md 5.8 KB
- reference/multi-character-scenes.md 4.6 KB
- reference/openai-gpt-image.md 26 KB
- reference/pricing.md 5.1 KB
- reference/transparent-backgrounds.md 7.4 KB
- scripts/crop_faces.py 3.3 KB runs code
- scripts/gemini-image.sh 7.0 KB runs code
- scripts/openai-image.sh 8.4 KB runs code
- scripts/README.md 10 KB
- scripts/rembg.sh 2.4 KB runs code
- templates/hero-image.md 7.7 KB
- templates/icon-set.md 5.4 KB
- templates/logo.md 5.0 KB
- templates/product-shot.md 8.6 KB
- templates/ui-dashboard.md 5.4 KB
- templates/ui-mobile.md 5.0 KB
- tests/test_crop_faces.py 539 B runs code
- tests/test_openai_image_prompt.py 2.4 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.
- 1mo ago Changed · +20 lines · +46 tokens per session 3912c87b963d
- 1mo ago Changed · -9 lines · +20 tokens per session 862415361304
- 2mo ago First seen · 166 lines · 107 tokens per session scan A c6cb445af402
image-generation is a skill published in the GitHub repository shaharsha/claude-skills (6 stars, last pushed today), licensed MIT. It adds 173 tokens to every session and 3,403 once invoked, about $0.0007 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 2026-08-31.
image-generation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| image-generationshaharsha/claude-skills | Skill | 6 | today | MIT | A | 173 | Claude Code |
| webgl-holographic-foilnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 41 | Claude Code, Codex |
| html-ppt-hermes-cyber-terminalnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 53 | Claude Code, Codex |
| html-ppt-taste-brutalistnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 78 | Claude Code, Codex |
| visual-ralphYeachan-Heo/oh-my-codex | Skill | 34k | 4d ago | MIT | A | 52 | Codex |
| glance-canonical-layoutsandroid/skills | Skill | 10k | yesterday | Apache-2.0 | A | 56 | Claude Code |
| accessibilitymicrosoft/hve-core | Skill | 1.6k | yesterday | MIT | A | 47 | Claude Code |