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Learn

OrganizationPopular
nanocoai
learn

Distill a reusable skill from anything — a directory, a URL, pasted notes, or what you just did together — or refine an existing skill with new learnings. Use when the user says '/learn', 'learn this', 'turn this into a skill', 'capture this workflow', 'make a skill from <source>', or 'improve/update the <name> skill'. Produces or updates a .claude/skills/<name>/SKILL.md authored to NanoClaw's skill guidelines. (This CREATES or REFINES a skill from a source; it does not install existing skills from a registry.)

Overview

Publishernanocoai
Repositorynanoclaw
Skill namelearn
Stars
30.9K
Forks
12.8K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nanocoai on GitHub. Read the source before you install it.

Installation

Install the Learn AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/learn
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/.claude/skills/learn .claude/skills/learn
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Learn in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Learn on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Learn is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Learn — Distill a Skill from Anything

Turn a source — a directory, a URL, pasted notes, or the work just done in this conversation — into a clean, reusable NanoClaw skill. The output is a new .claude/skills/<name>/SKILL.md (plus optional scripts/, references/, templates/) authored to the project's skill guidelines.

This skill is instruction-only: it uses the tools you already have (Read, Grep, Glob, WebFetch, Write) — there is no separate distillation engine and no reach-ins into core code.

When to use

Invoke when the user wants to capture a workflow as a reusable skill:

  • /learn <path> — read a project/dir and build a skill for working with it
  • /learn <url> — read docs / an API page and build a usage skill
  • /learn what we just did — distill the current conversation's workflow
  • /learn + pasted notes — turn notes into a structured skill

If the user instead wants to find and install an existing community skill, that is a different task — this skill creates new skills, it does not import them.

Workflow

1. Identify the source — and whether this is a new skill or a refine

  • A path → read the code/files.
  • A URL → fetch and read the page.
  • "what we just did" / "this" → use the current conversation as the source.
  • Pasted text → use it directly.

Then check .claude/skills/ for an existing skill that already covers this topic (the user may name it, e.g. "update the wow-on-steam-deck skill", or the subject may obviously match one). If one exists, this is a REFINE, not a fresh create — go to step 4's "Refining" branch.

If it is ambiguous what the skill should do, ask one clarifying question before proceeding.

2. Gather the material

  • Path: Glob the structure, Read the key files, Grep for the important entry points. Read enough to understand the repeatable procedure, not every line.
  • URL: WebFetch the page; pull out the concrete commands/steps, not the prose.
  • Conversation: re-read what was actually done — the commands, the gotchas, the decisions — and keep the parts that generalize.

3. Distill — find the reusable procedure

Strip the one-off specifics; keep the repeatable shape. A good skill answers: "Next time someone needs to do X, what are the exact steps, files, commands, and gotchas?" Capture:

  • the trigger / when-to-use,
  • the step-by-step procedure (commands, file paths, decision points),
  • the non-obvious gotchas that were hit — usually the most valuable part,
  • any scripts or templates worth shipping alongside.

4. Author the SKILL.md

Refining an existing skill? First Read the current .claude/skills/<name>/SKILL.md, then update it in place — do not blindly overwrite:

  • Keep what is still correct; weave the new learnings into the right sections.
  • Dedupe — don't append a near-duplicate step or a second gotcha that says the same thing.
  • Correct anything the new source proves stale (a changed path, command, or flag).
  • Preserve the existing name/folder and overall structure; the diff should read as a focused improvement, not a rewrite.

New skill? Write .claude/skills/<kebab-name>/SKILL.md.

Frontmatter (required):

yaml
---
name: <kebab-case, matches the folder>
description: "<what it does + when to use it + likely trigger phrases>"
---

description is what the agent reads to decide relevance — make it concrete and include the phrases a user would actually say.

Body: open with one paragraph on what the skill does, then a ## When to use section and a ## Workflow of numbered steps (the actual procedure). Use tables for command/file references, and add a short examples or troubleshooting section when the gotchas warrant it.

House authoring rules (from docs/skill-guidelines.md):

  • Additive, minimal reach-ins — prefer adding files; make the smallest possible edit to existing code, and only via single-line calls into skill-owned functions.
  • Instruction-only when possible — if Claude can do it by following prose plus existing tools, ship no code. These are the easiest skills to maintain and to merge.
  • If apply leaves anything behind, ship a REMOVE.md that fully reverses every change (no soft-disabled/commented-out removals).
  • If the skill adds an integration point in core code, add a test that goes red if the wiring is deleted or drifts.
  • Anti-patterns to avoid: separate VERIFY.md files, incomplete cleanup, raw SQL against core DBs, branch merges (use additive fetch), hand-maintained duplicate copies.

5. Place and verify

  • Write into .claude/skills/<name>/; confirm the folder name matches the name frontmatter and the YAML parses.
  • If feasible, dry-run the procedure the skill describes to confirm it is correct.
  • Tell the user the skill exists and how to invoke it (/<name>).

Example

/learn what we just did after a multi-step setup:

  1. Re-read the conversation's commands and gotchas.
  2. Distill the repeatable procedure.
  3. Write .claude/skills/<topic>-setup/SKILL.md with the steps, file paths, and the gotchas hit along the way.
  4. Report: "Created /<topic>-setup — invoke it next time to repeat this."

Notes

  • Keep skills focused — one capability per skill (mirrors the project's "one change per PR" rule).
  • The most valuable content is the gotchas, not the happy path.
  • This skill is prose and safe to re-run — use it again to refine an existing skill.

Frequently asked questions

What does the Learn AI skill do?

Distill a reusable skill from anything — a directory, a URL, pasted notes, or what you just did together — or refine an existing skill with new learnings. Use when the user says '/learn', 'learn this', 'turn this into a skill', 'capture this workflow', 'make a skill from <source>', or 'improve/update the <name> skill'. Produces or updates a .claude/skills/<name>/SKILL.md authored to NanoClaw's skill guidelines. (This CREATES or REFINES a skill from a source; it does not install existing skills from a registry.)

Why use Learn on TypingMind?

Because you install it once and use it with any model. Learn is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Learn in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/learn. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Learn?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Learn?

As many as you like. As long as a model supports skills, you can use Learn with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Learn AI skill free?

Yes. It is published on GitHub by nanocoai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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