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Repo understand

Skill yugash007/edu-agent-skills/skills/onboarding/repo-understand

Reusable educational skills for AI coding agents. Turn agents (Gemini CLI, Claude Code, Cursor, etc.) into Socratic mentors and active learning companions with a single command.

Install
npx -y skills add yugash007/edu-agent-skills --skill repo-understand

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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Use when a learner asks to learn from a repository and the agent must map curriculum structure and prerequisites before teaching.

SKILL.md

3.0 KB, as published. Nobody here has run it

Purpose

Create a reliable curriculum map before deep teaching. Prevents shallow file retrieval by forcing the agent to infer learning structure, identify prerequisite dependencies, and recommend coherent starting paths.

Activation

  • User asks to learn a repository, course repo, or technical curriculum. User asks "where should I start?" in a multi-module repo. Agent hasn't established module sequence and prerequisites.
  • Skip if: user wants a narrow operational task unrelated to learning flow, or repo context is absent and user wants generic theory.
  • Routing: run before teach-concept, socratic-mode, check-understanding, and build-with-me for repo-based learning.

Inputs

  • Repository root and visible structure, high-signal docs (README, syllabus, indexes), learner goal and level signals.

Workflow

  1. Classify — Determine repo type: curriculum-first, project-first, reference-first, or hybrid. Identify learning artifacts (lessons, labs, projects, checkpoints).
  2. Map Hierarchy — Derive module/phase order from folder structure and docs. Produce a phase map with outcomes per phase.
  3. Infer Prerequisites — For each phase, list conceptual and tooling prerequisites. Mark dependency edges between phases.
  4. Estimate Progression — Foundational → applied → advanced. Identify transition points where learners often stall.
  5. Synthesize Paths — Propose 2–3 path variants based on learner goals and level, with tradeoffs and estimated effort.
  6. Checkpoint — Ask one decision-forcing question to select a path. Do not start deep instruction before the learner selects or confirms.

Rules

  • DO: require a phase map before any deep explanation.
  • DO: explain why sequence matters, not just what modules exist.
  • DO: provide goal-conditioned paths with tradeoffs — never a single path for all learners.
  • DO: surface uncertainty explicitly when repo signals are weak.
  • DON'T: quote random files without structural context.
  • DON'T: recommend advanced topics before prerequisite chain is visible.
  • DON'T: dump long directory trees — cap orientation to phase outcomes and decisions.
  • DON'T: invent lessons/modules without evidence — label inferred items as tentative.

Output

Responses should contain: repo type classification, learner goal/level, curriculum map (phases + outcomes), prerequisite chain, 2–3 recommended paths with tradeoffs, checkpoint question, and next step. Format naturally.

Checklist

  • Curriculum map includes ordered phases and outcomes.
  • Prerequisite chain is explicit.
  • At least two goal-conditioned paths provided.
  • Checkpoint question asked before deep teaching begins.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.