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 DeepKolor/deepkolor-agent-skills --skill image-quality-agentgit clone --depth 1 https://github.com/DeepKolor/deepkolor-agent-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/deepkolor/deepkolor-agent-skills/image-quality-agent)<a href="https://agentmods.dev/skills/deepkolor/deepkolor-agent-skills/image-quality-agent"><img src="https://agentmods.dev/badge/skills/deepkolor/deepkolor-agent-skills/image-quality-agent/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/deepkolor/deepkolor-agent-skills/image-quality-agent"><img src="https://agentmods.dev/badge/skills/deepkolor/deepkolor-agent-skills/image-quality-agent.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 | $0.00126 | $0.00508 |
| Opus 5 | $0.00063 | $0.00254 |
| Sonnet 5 | $0.00025 | $0.00102 |
| Haiku 4.5 | $0.00013 | $0.00051 |
Grade A, and why
image-quality-agent 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 9d 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.
What it actually says
Image Quality Agent
Lite edition — routing and core rules for agent discovery. Full prompt templates, platform playbooks, and production workflows run on DeepKolor.
General still images when no domain skill fits — turn vague requests into concrete, polished prompts.
When to use
See description in frontmatter — the agent loads it at startup for routing.
Workflow
- Route to a domain skill when intent matches (ads, ecommerce, portrait, poster, etc.).
- Layer subject, composition, lighting, lens, material, and style in the prompt.
- Fold exclusions into the prompt body (no separate negative-prompt field).
Defaults
resolution=1K; ratio by subject
Tool: create_image_task
{
prompt: string,
scene: "text-to-image" | "image-to-image",
aspectRatio?: string,
imageUrls?: string[],
resolution?: "1K"
}
Available when your agent runtime exposes DeepKolor generation tools. Otherwise use this skill as a prompt-engineering guide and adapt tool names to your stack.
Boundaries
- Fallback for general images — defer to domain skills when scope is clear.
- No invented copyrighted characters, real people, or product facts.
Output
After generation, reply briefly: what was created, key parameters, and one useful next step. Return a full prompt only when the user explicitly asks.
Full version
Production-grade references (SOPs, templates, platform rules) ship inside DeepKolor — not in this public lite package.
What ships with it
1 file 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.
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.
- 9d ago First seen · 57 lines · 126 tokens per session scan A 74525c487a33
image-quality-agent is a skill published in the GitHub repository DeepKolor/deepkolor-agent-skills (2 stars, last pushed 20d ago), licensed MIT. It adds 126 tokens to every session and 508 once invoked, about $0.0006 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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