external/ui-ux-pro-max/brand/SKILL.md
Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.
npx skillsauth add seikaikyo/dash-skills brandInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Brand identity, voice, messaging, asset management, and consistency frameworks.
Inject brand context into prompts:
node scripts/inject-brand-context.cjs
node scripts/inject-brand-context.cjs --json
Validate an asset:
node scripts/validate-asset.cjs <asset-path>
Extract/compare colors:
node scripts/extract-colors.cjs --palette
node scripts/extract-colors.cjs <image-path>
# 1. Edit docs/brand-guidelines.md (or use /brand update)
# 2. Sync to design tokens
node scripts/sync-brand-to-tokens.cjs
# 3. Verify
node scripts/inject-brand-context.cjs --json | head -20
Files synced:
docs/brand-guidelines.md → Source of truthassets/design-tokens.json → Token definitionsassets/design-tokens.css → CSS variables| Subcommand | Description | Reference |
|------------|-------------|-----------|
| update | Update brand identity and sync to all design systems | references/update.md |
| Topic | File |
|-------|------|
| Voice Framework | references/voice-framework.md |
| Visual Identity | references/visual-identity.md |
| Messaging | references/messaging-framework.md |
| Consistency | references/consistency-checklist.md |
| Guidelines Template | references/brand-guideline-template.md |
| Asset Organization | references/asset-organization.md |
| Color Management | references/color-palette-management.md |
| Typography | references/typography-specifications.md |
| Logo Usage | references/logo-usage-rules.md |
| Approval Checklist | references/approval-checklist.md |
| Script | Purpose |
|--------|---------|
| scripts/inject-brand-context.cjs | Extract brand context for prompt injection |
| scripts/sync-brand-to-tokens.cjs | Sync brand-guidelines.md → design-tokens.json/css |
| scripts/validate-asset.cjs | Validate asset naming, size, format |
| scripts/extract-colors.cjs | Extract and compare colors against palette |
| Template | Purpose |
|----------|---------|
| templates/brand-guidelines-starter.md | Complete starter template for new brands |
$ARGUMENTS (first word)references/{subcommand}.mdtools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.