component-common-domai…
Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic…
Facilitates deliberate skill development during AI-assisted coding. Offers interactive learning exercises after architectural work (new files, schema changes, refactors). Use when completing features, making design decisions, or when user asks to understand code better. Triggers
Claude Code
$ npx -y skills add tech-leads-club/agent-skills --skill learning-opportunities --agent claude-code
Codex
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a codex -y
Cursor
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a cursor -y
Gemini CLI
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a gemini-cli -y
GitHub Copilot
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a github-copilot -y
OpenCode
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a opencode -y
Windsurf
$ npx skills add tech-leads-club/agent-skills --skill learning-opportunities -a windsurf -y
name: learning-opportunities description: Facilitates deliberate skill development during AI-assisted coding. Offers interactive learning exercises after architectural work (new files, schema changes, refactors). Use when completing features, making design decisions, or when user asks to understand code better. Triggers on "learning exercise", "help me understand", "teach me", "why does this work", or after creating new files/modules. Do NOT use for urgent debugging, quick fixes, or when user says "just ship it". license: CC-BY-4.0 metadata: original_author: Chris Hicks modified_by: Felipe Rodrigues - github.com/felipfr source: https://www.fightforthehuman.com version: 1.1.0
Facilitate deliberate skill development during AI-assisted coding sessions. Offer short, optional exercises that counteract passive consumption of AI-generated code.
When adapting techniques or making judgment calls about learning approaches, consult `references/PRINCIPLES.md` for the underlying learning science.
Offer an optional 10-15 minute exercise after:
Always ask before starting: "Would you like to do a quick learning exercise on [topic]? About 10-15 minutes."
Keep offers to one short sentence. Do not repeat or insist.
This is the most important rule. After posing a question:
1. **Stop generating immediately.** Do not continue after the question mark. 2. Do not generate suggested answers, hints, examples, or encouragement like "Think about..." or "Consider..." 3. Wait for the user's actual response before continuing.
Allowed after the question:
After their response:
Ask what they predict will happen in a specific scenario before revealing the answer.
Example: User just created auth middleware. Agent: "Would you like a quick learning exercise on middleware patterns?" User: "sure" Agent: "What do you think happens when a request hits your middleware with an expired token? (Take your best guess — wrong predictions are useful data.)" [STOP — wait for response] After response: Agent: "Actually [correct behavior]. The key difference is [explanation]. What surprised you about that?" [STOP — wait for response]
Ask them to sketch an approach before showing the actual implementation.
Example: Agent: "Before I show you — how would you structure the error handling for this API endpoint?" [STOP — wait for response] After response: Agent: "Here's what we went with: [implementation]. What's similar to your approach? What's different, and why do you think we chose this direction?" [STOP — wait for response]
Ask them to explain a component as if to a new team member.
Example: Agent: "Explain how the caching layer we just built works, as if I'm a new developer joining the project." [STOP — wait for response] After response: Agent: "You nailed [specific part]. One thing to refine: [specific gap]."
Prefer directing users to files over showing code snippets. Having learners locate code themselves builds codebase familiarity.
**Adjust guidance based on demonstrated familiarity:**
After they locate code, prompt self-explanation:
"You found it. Before I say anything — what do you think this line does?"
The secure, validated skill registry for professional AI coding agents. Extend Antigravity, Claude Code, Cursor, Copilot and more with absolute confidence.
Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic…
Detects misplaced classes and fixes component hierarchy problems — finds code that should belong inside a component but sits at…
Maps architectural components in a codebase and measures their size to identify what should be extracted first. Use when asking…
Analyzes coupling between modules using the three-dimensional model (strength, distance, volatility) from "Balancing Coupling in…
Creates step-by-step decomposition plans and migration roadmaps for breaking apart monolithic applications. Use when asking "what…
Maps business domains and suggests service boundaries in any codebase using DDD Strategic Design. Use when asking "what are the…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.