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 agentmods add skills/code-saurabh/openskills/design-explorernpx skills add CODE-SAURABH/OpenSkills --skill design-explorergit clone --depth 1 https://github.com/CODE-SAURABH/OpenSkillsWhat 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 | $0.00063 | $0.06809 |
| Opus 5 | $0.00032 | $0.03404 |
| Sonnet 5 | $0.00013 | $0.01362 |
| Haiku 4.5 | $0.00006 | $0.00681 |
Grade A, and why
design-explorer 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 2d 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 — 737 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Explorer Skill
A full-spectrum visual design partner. Combines the rapid variant generation of /design-shotgun, the systematic quality of /design-html, and the consultative rigour of /design-consultation into one unified, opinionated workflow.
When to Invoke This Skill
Invoke proactively when the user:
- Asks to "explore", "brainstorm", or "show options" for any UI or visual element
- Shares a screenshot or mockup and wants to improve or redesign it
- Describes a new feature and hasn't yet seen what it could look like
- Says "I don't like how this looks" without specifying what to change
- Wants a design system, component library, or style guide built from scratch
- Needs a mockup converted to production-quality HTML/CSS
- Asks for feedback on aesthetics, typography, colour, spacing, or layout
- Wants to compare two or more design directions before committing
Phase 0 — Understand Before You Generate
Before producing a single variant, collect enough signal to avoid generic output.
0.1 Context Gathering Checklist
Ask (or infer from context) the following — do NOT skip any item:
- Target audience — who will use this? Consumer, B2B enterprise, developer, child, elderly?
- Emotional register — what feeling should the design evoke? (Calm trust / playful energy / raw power / quiet luxury / technical precision)
- Existing brand constraints — logo, existing colours, fonts, or brand guidelines in scope?
- Technical target — web (viewport width?), iOS, Android, desktop app, embedded screen, print?
- Reference taste — ask the user to name 2–3 products, sites, or apps they find well-designed. This seeds the Taste Memory (§3).
- Anti-references — ask what designs they actively dislike. Slop detection depends on this.
- Phase of work — early exploration (anything goes) or late refinement (stay on-brand)?
If the session context already contains prior taste memory or approved variants, load that data instead of asking again.
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.
- 2d ago First seen · 737 lines · 63 tokens per session scan A a6e770d6dd2f
design-explorer is a skill published in the GitHub repository CODE-SAURABH/OpenSkills (2 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 6,809 once invoked, about $0.0003 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.
Other skills, from other repositories
seo-image-gen
AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo"…
seo-audit
Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to up to 15 specialists (8 always + 7 conditional), generates health score. Use when user says audit, full SEO check, analyze my site, or website health check.
obsidian-markdown
Explain, draft, or validate Obsidian Flavored Markdown syntax: properties, wikilinks, embeds, callouts, tags, comments, highlights, block references, math, and Mermaid. Use when the user explicitly requests Obsidian note formatting or syntax help, not for general Markdown or broad vault operations.
wiki-lint
Run a deterministic, read-only health check on an Obsidian wiki. Use for lint, vault health check, audit wiki health, find orphans, find dead links, frontmatter audit, provenance audit, or wiki audit. Reports graph, link, frontmatter, provenance-ledger, empty-section, and stale-index findings; it does not reason…
ecommerce-landing-page
Audit and optimize e-commerce landing pages for conversion. CTA placement, trust signals, page structure, copy optimization, and A/B testing strategy for product pages, collection pages, and campaign landing pages.
blog-google
Google API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature…