pf-ai-experience-patterns
Apply Red Hat's AI design language to AI-powered features — chatbots, assistants, generation UIs. Use when building AI experiences that should follow Red Hat brand and UX patterns.
What this skill does
# Red Hat AI Experience Design Patterns
This skill applies Red Hat's official design language for AI-enabled features (last updated February 2026). When building AI features, proactively apply these patterns to create transparent, polished, brand-compliant experiences.
**Authoritative source:** [https://staging.patternfly.org/ai/design-language](https://staging.patternfly.org/ai/design-language)
**Supporting files in this skill:**
- `guidelines/design-rules.md` — Detailed iconography, chatbot, color, and animation rules
- `guidelines/reference-mapping.md` — Reference image lookup tables for review findings
- `references/` — 21 extracted visual examples from key pages
- `references/REFERENCE-INDEX.md` — Descriptions of each reference image
## Core Principles
Every AI experience must follow these three principles:
1. **Be transparent** — Users want to know when they are interacting with AI. Make it clear using labels and visual cues.
2. **Make it personable, but not human** — AI should be polite and follow Red Hat voice and tone, but shouldn't act as though the user is interacting with a human.
3. **Stay within the Red Hat brand and design language** — Follow PatternFly and design system standards so AI experiences look and feel like Red Hat.
## Transparency Requirements
**Critical**: It should ALWAYS be clear when and how AI is being used.
- **Don't rely on just one indicator.** Use at minimum one visual AND one verbal indicator.
- Visual: Icons with AI sparkles, animations
- Verbal: "with AI", "AI-assisted", "AI-generated" in labels or button text
- **High-risk interactions**: Consider additional indicators (consult with AIA Reviewers)
**For AI-assisted features** (search, generation, editing): Place a transparency notice at the beginning of the experience. Minimum text: *"This feature uses AI technology. Do not include any personal information or other sensitive information in your input."* Include persistent notice: *"Always review AI-generated content prior to use."* Reference the Red Hat Privacy Statement.
**For virtual assistants/chatbots**: Show notice before user interacts and before any content is generated. Include an info icon (ℹ️) with persistent "Always review AI-generated content prior to use." Use AI icon + "AI" tag as visual and verbal indicators.
**For AI-generated content**: Must include a label AND icon indicating content was created using AI (e.g., Sparkle icon + "AI-assisted results" heading).
## Iconography Summary
Red Hat uses **9 official `rh-ui-icon-ai-*` icons** based on sparkles. Always pair icons with text ("...with AI", "...by AI"). Never create custom AI icons — request via #help-brand. See `guidelines/design-rules.md` for the full icon list and rules.
## Chatbot Summary
All chatbots must use **Red Hat's robot icon** as their avatar. Use PatternFly non-status color tokens for avatar colors. No gradients on launch buttons or chat message boxes. See `guidelines/design-rules.md` for full chatbot and chat message rules.
## Color & Animation Summary
Don't use color coding or gradients to indicate AI. AI features use the same colors as other interface elements. Use premade sparkle animations only — triggered on hover/click, loop once. See `guidelines/design-rules.md` for full color table and animation rules.
## Review Workflow
When analyzing a design against Red Hat AI patterns:
### Step 1: Identify what's being used
- What AI capabilities are shown? (generation, search, troubleshooting, chatbot, etc.)
- Are transparency notices present?
- Which icons are being used?
- Is this a chatbot (should use robot avatar) or another AI feature?
- Are there visual + verbal indicator pairs?
### Step 1a: Run a gradient sweep (required)
Before deciding compliance, inspect the full UI for gradients on AI-related surfaces:
- AI labels and badges (e.g., "AI Generated", "AI-assisted", "By AI")
- Chat launchers/buttons and any chatbot trigger controls
- Chat composer/message box borders, fills, and focus rings
- AI cards, panels, and highlighted callouts
- Any shimmer/glow treatment implying AI "thinking" or progress
If any of the above uses gradient color, mark as ❌ failed.
### Step 2: Categorize each requirement
- ✅ **Compliant** — Meets the guideline
- ❌ **Missing/Failed** — Does not meet the guideline
### Step 3: Select reference images for failed items
Read `guidelines/reference-mapping.md` to find the correct reference image for each failed check.
### Step 4: Summarize findings
Present a results table, then show the reference image for each ❌ item with a brief explanation of what needs to change.
**Results table format:**
| Category | Status |
| ------------ | ---------------- |
| [Check item] | ✅ Compliant |
| [Check item] | ❌ Missing/Failed |
**For each ❌ item**, show the reference image and explain what needs to change. Always show reference images for failed items so users can visually compare the correct pattern against their current implementation.
---
## Quick Reference Checklist
**Transparency:**
- At least one visual indicator (icon with sparkle)
- At least one verbal indicator ("with AI", "AI-assisted", etc.)
- Appropriate transparency notice for feature type
- "Always review AI-generated content prior to use" notice where applicable
**Iconography:**
- Using official `rh-ui-icon-ai-*` icons (not creating custom ones)
- Icons paired with text labels
- For chatbots: robot icon as avatar
**Color & Styling:**
- Using standard PatternFly/Red Hat colors
- No gradients on AI labels/badges, chat buttons/launchers, or chat message/composer boxes
- No gradients to indicate thinking/progress
- No special "AI colors"; follows existing color status associations
**Brand Compliance:**
- Follows PatternFly component patterns
- Personable but not human in tone
- Looks and feels like Red Hat
---
## Additional Resources
- **PatternFly AI Design Language** (authoritative source): [https://staging.patternfly.org/ai/design-language](https://staging.patternfly.org/ai/design-language)
- PatternFly ChatBot Extension: [https://staging.patternfly.org/extensions/chatbot/overview/design-guidelines](https://staging.patternfly.org/extensions/chatbot/overview/design-guidelines)
- PatternFly Colors: [https://staging.patternfly.org/foundations-and-styles/color](https://staging.patternfly.org/foundations-and-styles/color)
- Red Hat Design System: [https://ux.redhat.com/](https://ux.redhat.com/)
- Red Hat Brand Standards: [http://brand.redhat.com/](http://brand.redhat.com/)
- `@patternfly/react-icons` package: [https://www.npmjs.com/package/@patternfly/react-icons](https://www.npmjs.com/package/@patternfly/react-icons)
- Request new icons or animations: #help-brand on Slack
> Guidelines updated February 2026. This skill does not replace AI Assessment, Privacy Impact Assessment, or other required reviews.
---
*Remember: The goal is transparency. Users want to know when they're interacting with AI. Over-communicate rather than under-communicate.*
Related in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle 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 availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".