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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

Install / Use

npx skills add nanocoai/nanoclaw --skill learn

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Category

Automation

Supported Platforms

Claude Code

Tags

Our assessment of learn

learn scores 90/100 on our quality scale, 646th of 1,943 Automation skills we index (top 34%).

Its SKILL.md is 5.9 KB long, well organised into 10 sections with 1 code example: a thorough specification that gives an agent plenty to work with.

With 30,846 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
17/20
Description
15/15
Adoption
19/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 3 days ago, so learn is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

learn compared with similar skills

All 4 of these similar skills score higher than learn; compare them before choosing.

SkillScoreStarsUpdatedFormat
learn (this skill)by nanocoai9030.8k3d agoSKILL.md
Agent-Reachby Panniantong10085.7k12d agoCLAUDE.md
rufloby ruvnet10073.4ktodayCLAUDE.md
Scraplingby D4Vinci10084.0ktodayMCP Server
algorithmic-artby anthropics100177.9k5d agoSKILL.md

Frequently asked questions

How do I install learn?
Run npx skills add nanocoai/nanoclaw --skill learn. The install tabs above show the steps for each supported agent.
Which AI agents does learn work with?
It is written for Claude Code, as a SKILL.md file. Other agents that read the same format can often use it too.
Is learn safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is learn still maintained?
The repository was last updated 3 days ago, so learn is actively maintained.

name: learn description: "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.)"

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):

---
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.

Related Skills

View on GitHub
GitHub Stars30.8k
CategoryAutomation
Updated3d ago
Forks12.8k

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions