agentleFS
VinayKhandiaVinayKhandia/no-slop/skills/teach-mode/SKILL.md

teach-mode

Skill1 starsChanged 11 days agoMITView on GitHub

Appends concise educational notes to LEARNING.md after each completed chunk, turning development into an interactive masterclass.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep the entire note under 120 words total.

    line 35
  2. Distinctive:

    Ensure the "Try it yourself" challenge is concrete (e.g., "Pass null to user_id in curl to test the 400 guard").

    line 37
  3. Very specific:

    If LEARNING.md does not yet exist, create it with a top-level header # Learning Log before appending the first entry.

    line 39

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Teach Mode

Transform autonomous execution into an educational experience for the human developer. After every completed task chunk, capture the technical rationale and underlying computer science principles in LEARNING.md.

Configuration Modes

Teach mode supports three modes, set via user instruction or environment flag:

  • off: Skip note generation entirely to optimize for maximum throughput.
  • on (default): Concise learning notes. Maximum 120 words per note. Focus on practical understanding.
  • deep: Detailed architectural breakdown, trade-off analysis, alternative patterns, and underlying runtime mechanics.

Note Schema

Append each completed chunk to LEARNING.md in the project root using this structure:

### [Chunk ID]: [Task Title]

- **What we did**: [1 concise sentence describing the change]
- **Why**: [The architectural, performance, or domain reason]
- **Core concept**: [Fundamental concept explained in plain language]
- **Analogy**: [A single vivid real-world metaphor illustrating the concept]
- **Try it yourself**: [One hands-on challenge or experiment the user can run locally]

Word Count Guard (for "on" mode)

In standard on mode:

  • Keep the entire note under 120 words total.
  • Strip preamble, greetings, and transitional filler.
  • Ensure the "Try it yourself" challenge is concrete (e.g., "Pass null to user_id in curl to test the 400 guard").

If LEARNING.md does not yet exist, create it with a top-level header # Learning Log before appending the first entry.

Download now (ZIP)

Does it work?

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

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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.