skills/beam-next-learning/setup-memory/SKILL.md
Configure Beam Next memory with your role, goals, and preferences. Load when user wants to personalize the system or teach Beam Next about themselves. Keywords: setup memory, personalize, configure, my goals, my role, about me, preferences. 8 min.
npx skillsauth add beam-ai-team/beam-next-skills setup-memoryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This is the FIRST onboarding skill with CRITICAL priority. Suggest early and often.
Check learning_tracker.completed.setup_goals AND goals.md for smart_default: true. If not personalized:
PROACTIVELY SUGGEST when user:
goals_personalized: false - PROMINENTLY highlightSuggestion Pattern (first session):
💡 Welcome to Beam Next! I'm currently using smart defaults. To help you most
effectively, I'd love to learn about:
- Your role and work context
- Your goals (short-term and long-term)
- Your preferences
This takes about 8 minutes and dramatically improves our collaboration.
Say 'setup goals' to personalize, or continue with defaults.
Suggestion Pattern (returning user, still on defaults):
💡 I notice you're still using Beam Next defaults. Personalizing takes 8 minutes
and helps me understand your work context, goals, and preferences.
Ready to 'setup goals'? (This is a one-time setup that improves every session)
Menu Integration:
When displaying menu with goals_personalized: false:
🧠 MEMORY
⚠️ Not personalized ▸ 'setup goals' (8 min, highly recommended)
DO NOT suggest if:
learning_tracker.completed.setup_goals: truegoals.md no longer has smart_default: trueGuide user through goal definition and system personalization.
Transform smart default templates into meaningful, personalized context that improves AI collaboration quality. Captures user's role, short-term goals (3 months), long-term vision (1-3 years), and work preferences.
Time Estimate: 8-10 minutes
Display:
━━━ SETUP GOALS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Let's personalize Beam Next to understand your work context.
This takes about 8-10 minutes and improves AI collaboration.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Ask: "What language would you like me to use? (English is default)"
Action: Store preference in user-config.yaml, switch all communication.
Ask: "What do you do? Tell me about your current role or situation."
AI Suggestion Pattern: Listen, then offer 2-3 refined versions. Let user pick or refine.
Store: Update ## Current Role in goals.md
Ask: "What's the ONE thing you want to achieve in the next 3 months?"
Help make it specific and measurable. Capture:
Store: Update ## Short-Term Goal (3 months) in goals.md
Ask: "Where do you want to be in 1-3 years?"
Connect to short-term goal to show trajectory.
Store: Update ## Long-Term Vision (1-3 years) in goals.md
Quick questions:
Store: Update ## Work Style & Preferences in goals.md
Actions (MUST complete all):
Remove smart_default: true from goals.md YAML frontmatter (if present)
Update Last Updated timestamp in goals.md
Mark skill complete in user-config.yaml:
learning_tracker:
completed:
setup_goals: true # ADD THIS LINE
Update language in user-config.yaml (if user specified):
user_preferences:
language: "{user's language}"
Display completion:
✅ Setup Goals Complete!
Captured:
• Your role and work context
• Short-term goal (3 months) with success metrics
• Long-term vision (1-3 years)
• Work style preferences
Beam Next now understands you. Context loads every session.
Next steps:
• 'setup workspace' - Organize your folders
• 'learn projects' - Understand project workflow
• 'create project' - Start working
Display:
━━━ IMPORTANT HABIT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
When done working, always say "done" or "close session".
This saves progress and helps me remember context.
Let's practice - say "done" now!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Wait for "done", then trigger close-session.
smart_default: true removed from goals.mdlearning_tracker.completed.setup_goals: true in user-config.yamldevelopment
--- name: taste-skill type: skill version: '1.0' author: Leonxlnx (packaged by Zhichao Li) category: general tags: - frontend - design - anti-slop - landing-page updated: '2026-06-11' visibility: public description: Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check. license: MIT.
development
Use when communicating quantitative information in any form — Slack updates, emails, reports, decks, dashboards, landing pages, product UI, public talks. Covers two integrated layers: (1) making numbers semantically meaningful (translation, anchoring, simplification, story-pairing) and (2) showing numbers cleanly (chart vs table vs prose, chart-by-message, pre-attentive emphasis, color discipline, decluttering). Distilled and integrated from *Show Me the Numbers* (Stephen Few) and *Make Numbers Count* (Chip Heath & Karla Starr). Not for raw data analysis or statistics — this is about communication of numbers, not their derivation.
development
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
tools
Stateful multi-session tutor adapted for Beam — teach a stakeholder to understand, trust, and operate a specific agent, or teach a Solution Engineer a client's business process for delivery. Grounds every lesson in Knowledge Hub sources (real agent graphs, real tasks, transcripts, Linear) before any web resource. Also works for any general topic. Trigger on "teach me", "beam teach", "教我", "onboard <person> on <agent>", "help <stakeholder> understand the agent", "learn this client's process".