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 Oriolshhh/runware-image-mcp --skill spec-frontendgit clone --depth 1 https://github.com/Oriolshhh/runware-image-mcpWrote 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/oriolshhh/runware-image-mcp/spec-frontend)<a href="https://agentmods.dev/skills/oriolshhh/runware-image-mcp/spec-frontend"><img src="https://agentmods.dev/badge/skills/oriolshhh/runware-image-mcp/spec-frontend/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/oriolshhh/runware-image-mcp/spec-frontend"><img src="https://agentmods.dev/badge/skills/oriolshhh/runware-image-mcp/spec-frontend.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 | $0.00020 | $0.01690 |
| Opus 5 | $0.00010 | $0.00845 |
| Sonnet 5 | $0.00004 | $0.00338 |
| Haiku 4.5 | $0.00002 | $0.00169 |
Grade A, and why
spec-frontend 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 8d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/spec-frontend — Specify a substantial existing-frontend redesign
Purpose
Turn an existing page, route, or flow into a detailed, product-specific redesign specification before code changes begin.
Use this when /improve-ui-ux would be too small: the goal is a material
improvement to hierarchy, visual craft, interaction, and usability while
preserving intended product behavior and valuable brand equity.
Invocation
/spec-frontend <route/component and desired outcome>
Accepted input
An existing rendered route or component, pain points, screenshots or references, target users, desired degree of change, brand constraints, and success criteria.
Prerequisites
A HarnessKit workspace and an existing frontend surface. A runnable preview is strongly preferred; static-only planning must be labelled lower confidence.
Procedure
- Apply
context-discovery. Identify the exact surface, user, primary task, product goal, requested degree of change, preservation constraints, non-goals, preview command, stable fixture/data, supported themes, and relevant viewports. - Inspect repository evidence before asking questions. Ask one grouped batch of only decision-changing questions, normally no more than three and never more than five. If the user requests a dramatic change, clarify what must remain recognizable rather than treating “drastic” as permission to replace everything.
- Apply the complete curated skill set, loading each canonical body rather than
fetching upstream prompts at runtime:
frontend-design-direction,visual-craft,design-system-integration,ui-state-design,responsive-ui-engineering,accessible-ui-engineering,motion-design, andbrowser-visual-validation. - Run a discovery wave using native isolated subagents in parallel when the
active tool supports them:
visual-qa-testerrecords a reproducible baseline with like-for-like route, data, state, viewport, theme, task steps, console, and network conditions;design-system-specialistmaps tokens, typography, icons, primitives, components, themes, states, and closest precedents. Otherwise use clearly labelled native-sequential or simulated-sequential passes. Record the actual execution mode; never imply independence that did not exist.
- Give the same brief, context capsule, baseline, and reuse map to independent
read-only specialist passes. Do not show them each other's first conclusions:
ux-reviewer: task flow, comprehension, copy, information architecture, friction, recovery, and state completeness;visual-craft-specialist: hierarchy, typography, color, spacing, gaps, density, optical alignment, shape, elevation, imagery, icons, and anti-AI-slop;interaction-design-specialist: buttons and controls, feedback, focus, async states, interruption, gestures, and purposeful motion;accessibility-reviewer: semantic, keyboard, focus, contrast, zoom/reflow, reduced-motion, form, and recovery constraints.
- Have
frontend-design-leadsynthesize—not vote—one recommended direction. Offer two only for a genuine unresolved product/brand fork. Preserve material dissent and explain why the selected direction fits the user outcome. - Inspect active packs before continuing. If more than one primary aesthetic
pack is enabled, stop and ask the user to choose exactly one; exporter
priority does not make contradictory directions coherent. Otherwise use at
most one explicitly enabled primary aesthetic pack:
frontend-design,taste-skill, orui-ux-pro-max. The optionalemil-design-engineeringlayer may supplement interaction craft. Do not silently enable packs, blend competing voices, execute upstream scripts, or copy a source skill's stack/dependency recommendations over repository evidence. - Write
.agent/specs/<kebab-case-name>.mdas an ordinary valid HarnessKit spec using the required frontmatter below. Include:- baseline evidence and named user outcome;
- preservation constraints, non-goals, and rejected alternatives;
- selected design thesis and anti-AI-slop acceptance rubric;
- content and hierarchy;
- typography roles, scale, weight, line height, and measure;
- semantic color roles, themes, contrast, and non-color cues;
- spacing/density/grid, alignment, radius, borders, elevation, imagery, and icons;
- responsive transition rules based on content pressure;
- complete operational and control-state matrices;
- interaction/motion purpose, timing behavior, interruption, reduced motion, pointer/touch/keyboard behavior, and performance acceptance;
- accessibility contract;
- design-system reuse and narrowly justified extensions;
- dependency-ordered implementation tasks, files/ownership, tests, browser scenarios, fixtures, viewports, gates, risks, and approval needs.
- Present a
/sum-spec-style plain-language summary and stop for explicit approval. Do not launch implementation workers or edit production 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.
- 8d ago First seen · 152 lines · 20 tokens per session scan A 41a675c2e728
spec-frontend is a skill published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 1,690 once invoked, about $0.0001 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 2026-09-03.
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