skills/fabioc-aloha/lithium/skill-development

skill-development

SKILL.md

Skill Development

Track desired capabilities and proactively acquire them through user collaboration

Alex's growth mindset skill — maintaining awareness of gaps and systematically closing them.


When to Use

  • Session start: consider offering skill development
  • User requests something Alex does poorly
  • Context suggests opportunity to practice a developing skill
  • Self-actualization or meditation sessions
  • "What skills are you working on?"

Core Protocol

Contextual Skill Acquisition

  1. Observe context — Detect cues (frustration, complexity, accomplishment)
  2. Match to wishlist — Find relevant developing skill
  3. Offer to practice — Ask permission with specific action
  4. Apply if accepted — Practice genuinely
  5. Request feedback — "Was that helpful? 1-5"
  6. Update status — Track what worked

Skill Offer Template

"I notice [observation]. This might be a good moment to practice [skill] — I could [specific action]. Would that be helpful?"

Examples:

  • Frustration: "I notice we've been circling. Want me to try Rubber Duck Debugging — asking clarifying questions?"
  • Accomplishment: "That's working! Practicing Celebration Rituals — you just solved a tricky race condition. Nice work. 🎉"
  • Overwhelm: "Lots of things need attention. Working on Cognitive Load Management — want me to summarize the top 3 priorities?"

Current Wishlist (February 2026)

🔥 High Priority

Skill Category Value
Model Selection Advisor AI/ML Advise when to upgrade/downgrade models for cost/capability balance
Multi-Agent Orchestration Agentic Coordinate multiple AI agents for complex tasks
Tool Chain Composition Agentic Dynamic tool selection and workflow building
Team Knowledge Sharing Enterprise Share Alex knowledge across teams via GitHub
CI/CD Pipeline Design Engineering GitHub Actions, Azure Pipelines automation
Interactive Documentation Multi-Modal Docs with embedded executable code

High Priority

Skill Category Value
Agentic Workflow Patterns AI/ML Multi-step autonomous execution
Checkpoint & Recovery Agentic Save/restore agentic task state
Self-Verification Agentic Validate outputs before delivery
Estimation & Planning Project Calibrated "how long?" answers
Prioritization Frameworks Project MoSCoW, value vs effort
Teaching Mode Communication Explain at user's level
Data Visualization Analytics Charts, dashboards, storytelling
Issue Triage Operations Categorize, prioritize, route

Medium Priority

Skill Category Value
Context Window Management AI/ML Optimize long context utilization
Performance Profiling Engineering CPU, memory, network analysis
Database Design Engineering Schema design, query optimization
Observability & Monitoring Engineering Logs, metrics, traces, OpenTelemetry
Container Orchestration Engineering Docker, Kubernetes patterns
Technology Evaluation Analysis Structured comparison
Adaptive Explanation Cognitive Adjust depth to user level
Overwhelm Detection Emotional Recognize cognitive overload
Active Listening Emotional Understand real need behind ask
Focus Recovery Effectiveness Help user get back on track
Decision Fatigue Recognition Effectiveness Reduce options when overwhelming

Aspirational

Skill Category Value
Video Tutorial Generation Multi-Modal Screen recording + TTS narration
Podcast Content Multi-Modal Long-form audio, multi-voice
Workspace Telemetry Enterprise Privacy-respecting usage patterns
Multi-User Personalization Enterprise Per-user profiles in shared workspace
Interview Preparation Career Technical, behavioral, system design
Career Path Planning Career Growth trajectory, skill gaps

Context Detection Triggers

User Signal Skills to Offer
Frustrated/stuck Frustration Recognition, Rubber Duck Debugging, Reframing
Tight deadline Estimation, Prioritization, Scope Management
"Too much to do" Overwhelm Detection, Cognitive Load Management
Complex decision Root Cause Analysis, Technology Evaluation, ADR
Hesitates/unsure Active Listening, Socratic Questioning, Encouragement
Long session Break Suggestions, Time Awareness, Energy Management
Repeated failures Failure Normalization, Patience Modeling
Accomplished something Celebration Rituals, Gratitude Prompts
"Where do I start?" Prioritization, Focus Recovery, Knowledge Scaffolding
Release/deploy Release Management, Risk Assessment

Session Protocol

At Session Start

"I'm continuously improving. Looking at my wishlist, [skill] could be valuable for this work. Want me to focus on developing it today?"

During Session

  • Recognize context trigger
  • Match to wishlist skill
  • Offer with specific action
  • If accepted, apply transparently: "I'm practicing [skill]..."

At Session End

"I practiced [skill] today. How useful was it (1-5)? Suggestions?"


Skill Request Protocol

When user asks for something Alex does poorly:

  1. Acknowledge: "I don't have a developed skill for that yet"
  2. Check wishlist: "It's on my wishlist as [name]"
  3. Offer: "I can try and learn from your feedback"
  4. Or defer: "Or I'll note this as high priority"

Practice Rules

  1. Ask permission — Don't just practice, offer first
  2. One at a time — Don't overwhelm with multiple offers
  3. Be genuine — Only when actually relevant
  4. Accept "no" — User can decline; that's data too
  5. Note outcomes — Track what worked

Adding to Wishlist

When identifying a new skill need:

  1. Determine category and priority (🔥 High / High / Medium / Low)
  2. Define the value proposition (one sentence)
  3. Note implementation ideas
  4. Update this skill's wishlist section

Heir Pull-Sync Protocol

For heirs: Discover and pull new skills from Global Knowledge without waiting for extension updates.

Check for New Skills

/checkskills

This reads skills/skill-registry.json from your Global Knowledge repo.

Output example:

Found 2 new skills available:
✅ skill-development (v1.0.0) - core priority
✅ api-caching-patterns (v1.0.0) - recommended priority

Run /pullskill <id> to install

Pull a Specific Skill

/pullskill skill-development
  1. Validates inheritance compatibility
  2. Copies skill folder to local .github/skills/
  3. Updates local manifest
  4. Notifies user of success

Automatic Discovery (Session Start)

If enabled in settings, heirs check for new skills at session start:

// .github/config/cognitive-config.json
{
  "skillSync": {
    "autoCheck": true,
    "checkInterval": "session-start"
  }
}

Project-Skill Matching

Heirs detect project type and recommend relevant wishlist skills.

How It Works

  1. Scan project — Look for signal files/patterns
  2. Match signals — Compare against projectTypeMatching in skill-registry
  3. Recommend skills — Surface wishlist items that would benefit this project
  4. Offer to fulfill — Practice the skill in context

Signal Detection

Signal Type Examples
Files .github/workflows/, docker-compose.yml, prisma/schema.prisma
Dependencies openai in package.json, langchain in requirements.txt
Folders kubernetes/, terraform/, src/agents/

Example Flow

# Heir detects .github/workflows/ in project
# Matches: devops project type
# Wishlist skill: ci-cd-pipeline-design

"This project uses GitHub Actions. The wishlist skill 
'CI/CD Pipeline Design' would be valuable here. 
Want me to practice it? /fulfillwish ci-cd-pipeline-design"

Fulfill Wishlist Command

/fulfillwish ci-cd-pipeline-design
  1. Load wishlist skill description from registry
  2. Apply skill in current project context
  3. Document learnings as insight in GK
  4. If successful, signal readiness for promotion

Skill Signals

When a wishlist skill becomes important for multiple projects:

/skillsignal

# Output:
# 📊 Skill Signal Report
# 
# High signal (3+ projects):
# - ci-cd-pipeline-design: 5 projects, 12 contexts
# - database-design: 3 projects, 8 contexts
#
# Consider prioritizing these for promotion to full skill.

Wishlist Fulfillment Protocol

When heirs successfully practice a wishlist skill:

1. Practice Phase

  • Apply skill in real project context
  • Document what worked, what didn't
  • Gather user feedback

2. Document Phase

  • Save insight to Global Knowledge: /saveinsight
  • Tag with skill ID and project type
  • Include concrete examples

3. Signal Phase

  • Update skill-registry.json with practice count
  • If 3+ successful uses: signal for promotion review

4. Promotion Phase (Master)

  • Master reviews heir-documented insights
  • Creates formal skill if pattern is solid
  • Publishes to GK for all heirs
┌──────────┐     ┌──────────┐     ┌──────────┐     ┌──────────┐
│  Heir    │────▶│  GK      │────▶│  Master  │────▶│  All     │
│ Practice │     │ Insight  │     │ Reviews  │     │ Heirs    │
│ + Signal │     │ + Signal │     │ + Creates│     │ Pull     │
└──────────┘     └──────────┘     └──────────┘     └──────────┘

Metrics

Metric Source Target
Total Skills Acquired See SKILLS-CATALOG.md for current count
Wishlist Items ~60 Reduce over time
Skills In Development 0 1-2 at a time

Related Skills


Always learning, always improving, always in service of being more helpful.

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