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 seb1n/awesome-ai-agent-skills --skill wireframinggit clone --depth 1 https://github.com/seb1n/awesome-ai-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/seb1n/awesome-ai-agent-skills/wireframing)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/wireframing"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/wireframing/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/seb1n/awesome-ai-agent-skills/wireframing"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/wireframing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.03062 |
| Opus 5 | $0.00023 | $0.01531 |
| Sonnet 5 | $0.00009 | $0.00612 |
| Haiku 4.5 | $0.00005 | $0.00306 |
Grade A, and why
wireframing 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Wireframing — 97% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wireframing
This skill enables the agent to produce wireframes at three fidelity levels — low-fi (block layouts and content hierarchy), mid-fi (defined components with placeholder content), and high-fi (pixel-accurate specs with real content, spacing values, and interaction notes). Since the agent works in text, wireframes are rendered as ASCII/box-drawing layouts or structured component specifications with precise dimensions. Each wireframe includes a component inventory, interaction annotations, and responsive breakpoint behavior.
Workflow
-
Clarify the Screen and Its Purpose: Identify which screen or view to wireframe, its role in the user flow, and the primary user action on that screen. Determine the target platform (desktop web, tablet, mobile) and any framework constraints (e.g., Bootstrap grid, Material Design components). This scoping prevents wireframes from growing beyond their intended focus.
-
Define the Component Inventory: List every UI component the screen requires: navigation bars, headings, cards, forms, buttons, tables, modals, tooltips, empty states, and loading states. For each component, note its content requirements (label text, data fields, image dimensions) and its interactive behavior (clickable, expandable, draggable, editable). This inventory becomes the wireframe's bill of materials.
-
Create the Low-Fidelity Layout: Produce a block-level layout showing content zones and their spatial relationships. Use ASCII box drawing to represent regions. Focus on information hierarchy: what the user sees first, second, third. Do not specify exact pixel values or real content at this stage — use labels like
[Hero Image],[Product Grid 3×2],[CTA Button]. -
Elevate to Mid-Fidelity: Replace placeholder labels with representative content. Add specific component types (dropdown vs. radio, text input vs. textarea), define column counts and approximate proportions, and note key spacing relationships (e.g., "16px gap between cards"). Include navigation states (active tab, breadcrumb trail) and basic content hierarchy (heading levels, body text, captions).
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.
- 11d ago First seen · 167 lines · 45 tokens per session scan A ee7bae326553
wireframing is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 3,062 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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