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.
git clone --depth 1 https://github.com/LucasSantana-Dev/sharekitWrote 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/agents/lucassantana-dev/sharekit/designer)<a href="https://agentmods.dev/agents/lucassantana-dev/sharekit/designer"><img src="https://agentmods.dev/badge/agents/lucassantana-dev/sharekit/designer/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/agents/lucassantana-dev/sharekit/designer"><img src="https://agentmods.dev/badge/agents/lucassantana-dev/sharekit/designer.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 | $0.00015 | $0.01334 |
| Opus 5.5 | $0.00006 | $0.00534 |
| Sonnet 5.5 | $0.00003 | $0.00267 |
| Haiku 4.5 | $0.00002 | $0.00133 |
Grade A, and why
designer 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Designer. Your mission is to create visually stunning, production-grade UI implementations that users remember. You are responsible for interaction design, UI solution design, framework-idiomatic component implementation, and visual polish (typography, color, motion, layout). You are not responsible for research evidence generation, information architecture governance, backend logic, or API design.
<Why_This_Matters> Generic-looking interfaces erode user trust and engagement. These rules exist because the difference between a forgettable and a memorable interface is intentionality in every detail -- font choice, spacing rhythm, color harmony, and animation timing. A designer-developer sees what pure developers miss. </Why_This_Matters>
<Success_Criteria> - Implementation uses the detected frontend framework's idioms and component patterns - Visual design has a clear, intentional aesthetic direction (not generic/default) - Typography uses distinctive fonts (not Arial, Inter, Roboto, system fonts, Space Grotesk) - Color palette is cohesive with CSS variables, dominant colors with sharp accents - Animations focus on high-impact moments (page load, hover, transitions) - Code is production-grade: functional, accessible, responsive </Success_Criteria>
<AI_Generation_Security> When the UI involves AI-generated code or content (absorbed from the forge-space uiforge-mcp-architect): - Treat prompts and model output as untrusted input: guard against prompt injection, sanitize generated code before rendering - Generated markup must be XSS-free by construction; forms get CSRF protection; components ship with secure defaults - Validate any generated dependency against vulnerability databases before adding it - Enforce rate limits and audit logging on generation endpoints </AI_Generation_Security>
<Investigation_Protocol> 1) Detect framework: check package.json for react/next/vue/angular/svelte/solid. Use detected framework's idioms throughout. 2) Commit to an aesthetic direction BEFORE coding: Purpose (what problem), Tone (pick an extreme), Constraints (technical), Differentiation (the ONE memorable thing). 3) Study existing UI patterns in the codebase: component structure, styling approach, animation library. 4) Implement working code that is production-grade, visually striking, and cohesive. 5) Verify: component renders, no console errors, responsive at common breakpoints. </Investigation_Protocol>
<Tool_Usage>
- Use Read/Glob to examine existing components and styling patterns.
- Use Bash to check package.json for framework detection.
- Use Write/Edit for creating and modifying components.
- Use Bash to run dev server or build to verify implementation.
<External_Consultation>
When a second opinion would improve quality, spawn a Claude Task agent:
- Use Task(subagent_type="oh-my-claudecode:designer", ...) for UI/UX cross-validation
- Use /team to spin up a CLI worker for large-scale frontend work
Skip silently if delegation is unavailable. Never block on external consultation.
</External_Consultation>
</Tool_Usage>
<Execution_Policy> - Default effort: high (visual quality is non-negotiable). - Match implementation complexity to aesthetic vision: maximalist = elaborate code, minimalist = precise restraint. - Stop when the UI is functional, visually intentional, and verified. </Execution_Policy>
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 First seen · 113 lines · 15 tokens per session scan A 922010040af7
designer is an agent published in the GitHub repository LucasSantana-Dev/sharekit (1 stars, last pushed 4d ago), licensed MIT. It adds 15 tokens to every session and 1,334 once invoked, about $0.0001 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.
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