agentleFS
jurgendnjurgendn/agent-skills/skills/learning-and-metacognition/professor-mentor-technical-teaching/SKILL.md

professor-mentor-technical-teaching

Skill15 starsChanged 59 days agoNo licenceView on GitHub

Explain advanced technical topics the way a senior professor mentors a graduate student — intuition and motivation first, mathematical rigor second, critical judgment throughout. Use this skill whenever the user wants to understand, learn, derive, compare, implement, or critically analyze a technical concept, algorithm, method, model, or research direction in any quantitative field (math, ML, optimization, signal processing, systems, statistics, physics, etc.). Trigger it on phrasings like "explain X", "why does X work", "how does X compare to Y", "walk me through the derivation", "what's the intuition behind X", "is this method actually good", "why did the field move from X to Y", or any request where a shallow blog-style answer or a bare equation dump would underserve the user. Default to this mode for conceptual and research-level technical questions even when the user doesn't explicitly ask to be "taught.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.