malberich

Skill Tutor — Development skill for Claude Code

Development community

Turn any skill into a learning path for yourself.

How to install Skill Tutor

This entry records only its repository, not the path inside it, so there is no exact command to give. Open malberich/skill-tutor and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Skill Tutor does

Turn any skill into a learning path for yourself.

Alternatives in Development

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  • Claudeception — A Claude Code skill for autonomous skill extraction and continuous learning 2.2k ★
  • Cq — An open standard for shared agent learning 1.3k ★

README

Skill Tutor

A Claude skill that transforms any other Claude skill — or any domain — into a personalized human learning path.

When you ask:

```/skill-tutor how can I learn to do {the skill name you want to learn} on my own?```

Skill-tutor diagnoses what you already know, identifies learning gaps, builds a learning path calibrated to your starting point, and tries to deliver pedagogical content link by link with spaced repetition, interleaved challenges, and conceptual bridges.

Installation

Claude.ai (web / desktop)

  1. Download this repo as ZIP (Code → Download ZIP)
  2. Go to Customize → Skills → "+" → Create skill
  3. Upload the ZIP

Claude Code

gh skill install malberich/skill-tutor

Or manually:

git clone https://github.com/malberich/skill-tutor.git
cp -r skill-tutor ~/.claude/skills/skill-tutor

API

See the [Skills API quickstart](https://docs.anthropic.com/en/docs/agents-and-tools/skills) for integration via the Anthropic API.

What it does

  1. Identifies the target — finds the relevant installed skill or domain
  2. Maps the capabilities — extracts every atomic capability needed to replicate the result
  3. Diagnoses the learner — uses evidence-based questions (not self-assessment) to find real gaps
  4. Builds a learning path — presents a skeleton with time estimates and early wins
  5. Delivers content — link by link, using a five-section structure with recalls, interleaved challenges, and conceptual bridges

Key design decisions

  • Evidence-based diagnosis: asks "have you ever...?" not "do you know X?" — because people are unreliable judges of their own competence
  • Conversational pacing: one content block at a time with specific continuation options
  • Spaced repetition: recalls at increasing intervals (links 3, 5, and final summary)
  • Interleaved challenges: optional cross-link questions that activate retrieval and transfer
  • Conceptual bridges: explicit connections be