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 evoelsewhere/evoflux --skill image-to-codegit clone --depth 1 https://github.com/evoelsewhere/evofluxWrote 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/evoelsewhere/evoflux/image-to-code)<a href="https://agentmods.dev/skills/evoelsewhere/evoflux/image-to-code"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/image-to-code/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/evoelsewhere/evoflux/image-to-code"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/image-to-code.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 | $0.00034 | $0.00666 |
| Opus 5 | $0.00017 | $0.00333 |
| Sonnet 5 | $0.00007 | $0.00133 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
image-to-code 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 3d 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.
This is a copy
100% identical to image-to-code — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image to Code
Translate a selected visual target into a high-quality frontend. Read ../index/SKILL.md, ../../references/critical-overrides.md, and the relevant saved context from ../user-context/SKILL.md before building.
Preconditions
- Require an unambiguous selected image, screenshot, mockup, generated result, or design frame. A written brief alone is not a visual target; route to ideation first when appropriate.
- Resolve which image is selected before editing. Ask when an ordinal or attachment is ambiguous.
- Use only the current task's relevant product context, tokens, components, assets, and references.
Workflow
- Inspect the source visual at useful detail and record its viewport, layout regions, hierarchy, spacing, typography, colors, borders, radii, shadows, imagery, icons, responsive behavior, and visible states.
- Inventory every required asset. Reuse supplied or repository assets when they match. Use an available image-generation tool for custom raster imagery and an appropriate existing icon set for UI icons. Do not substitute emoji, generic placeholders, or improvised CSS drawings for meaningful visual assets.
- Inspect the target repository and use its existing framework, package manager, component system, design tokens, and conventions. React is not required. Do not replace an established stack merely to match this workflow.
- If no target app exists, create the smallest runnable frontend supported by the harness and suited to the request; plain HTML/CSS/JavaScript is acceptable.
- Implement the full visible structure and the primary user journey. Unless requested otherwise, make navigation, tabs, menus, forms, toggles, selections, and main calls to action behave realistically without inventing backend systems.
- Match desktop or mobile based on the source. When the source is a phone UI and no device is named, verify around 390 × 844 as well as any relevant responsive behavior.
- Run the real app using its normal development or preview command.
- Capture the implementation using the browser tool selected by
../index/SKILL.mdand run../design-qa/SKILL.mdagainst the source visual. - Fix all blocking and high-impact mismatches. Save
design-qa.mdin the project root and hand off only when it recordsfinal result: passed, or clearly report a genuine capture/verification blocker.
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.
- 3d ago First seen · 40 lines · 34 tokens per session scan A b887ae459ff4
image-to-code is a skill published in the GitHub repository evoelsewhere/evoflux (7 stars, last pushed yesterday), licensed Apache-2.0. It adds 34 tokens to every session and 666 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to image-to-code, differing in 0 lines, and is treated as a copy.
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