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Agent skill

Skill Distiller

by nanocoai in nanocoai/nanoclaw

Turns a directory, URL, pasted notes or the work just done in the session into a reusable skill file, or refines a skill that already exists.

MITAuto-check passedAgent Workflows

Install Skill Distiller

skills CLI
$ npx skills add nanocoai/nanoclaw --skill learn -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nanocoai/nanoclaw learn --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nanocoai/nanoclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/learn .claude/skills/learn && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
learn
GitHub stars
31k
Token cost
~1.5k tokens
SKILL.md length
789 words
Files
1
Skills in repo
59
Repo updated
First seen
Licence
MIT

At a glance

Turns a directory, URL, pasted notes or the work just done in the session into a reusable skill file, or refines a skill that already exists.

  • Works in 5 steps: Identify the source — and whether this… → Gather the material → Distill — find the reusable procedure → …
  • Capturing a workflow you just completed as a reusable skill
  • SKILL.md covers When to use, Workflow, Example and Notes
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

You point it at a source, and the agent reads the code, fetches the page, or re-reads the conversation to find the repeatable procedure. It strips one-off specifics and keeps the trigger, the steps, commands, file paths, decision points and known gotchas, then writes a new SKILL.md under .claude/skills following NanoClaw's skill guidelines, with optional scripts, references and templates folders.

Before creating anything it checks the skills folder for one that already covers the topic; if there is one, the run becomes a refinement rather than a new skill. It asks a single clarifying question when the intended behavior is ambiguous. No extra engine is involved, since it uses the standard Read, Grep, Glob, WebFetch and Write tools, and it does not install community skills from a registry.

When your agent uses it

  • Capturing a workflow you just completed as a reusable skill
  • Turning API documentation from a URL into a usage skill
  • Updating an existing skill with lessons learned
  • Converting pasted notes into a structured skill

Example prompts

  • “/learn what we just did, so next time the release steps are a skill.”
  • “Read ./tools/deploy and build a skill for deploying with it.”
  • “Update the deploy skill with the rollback gotcha we hit today.”

Requirements

  • A project with a .claude/skills folder
  • Network access when the source is a URL

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Identify the source — and whether this is a new skill or a refine
  2. Gather the material
  3. Distill — find the reusable procedure
  4. Author the SKILL.md
  5. Place and verify

What it can do on your machine

Read from SKILL.md and the folder at commit 66f0823. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Distiller loads about 1.5k tokens when it runs. Until then it costs about 131 tokens; SKILL.md has 789 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~131
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from nanocoai/nanoclaw at commit 66f0823, republished under its MIT licence (© nanocoai). 789 words, ~1,511 tokens.

Download SKILL.mdSave it as .claude/skills/learn/SKILL.md (or your agent's skills folder).
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.
Show full SKILL.md (400 more words)Show less
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.

© nanocoai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/learn of nanocoai/nanoclaw.

Open the folder on GitHubat commit 66f0823

Compare with similar skills

Skill Distiller next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Distiller compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Distiller this skillnanocoai/nanoclaw31k—~1.5kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79489 repos~8.2kAutomated safety check: PassApache-2.0
Claude Code Skill Developer Guidediet103/claude-code-infrastructure-showcase10k10 repos~3.5kAutomated safety check: PassMIT
Darwin Skill Optimizeralchaincyf/darwin-skill6.2k1 repos~4.7kAutomated safety check: PassMIT
Claude Code Command Developmentanthropics/claude-plugins-official37k10 repos~4.8kAutomated safety check: PassApache-2.0
Claude Code Plugin Structureanthropics/claude-plugins-official37k10 repos~3.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Skill Distiller

What does Skill Distiller do?

Turns a directory, URL, pasted notes or the work just done in the session into a reusable skill file, or refines a skill that already exists. You point it at a source, and the agent reads the code, fetches the page, or re-reads the conversation to find the repeatable procedure.claude/skills following NanoClaw's skill guidelines, with optional scripts, references and templates folders.

When should I use Skill Distiller?

Skill Distiller fits situations like: capturing a workflow you just completed as a reusable skill; turning API documentation from a URL into a usage skill; updating an existing skill with lessons learned; converting pasted notes into a structured skill.

How do I install Skill Distiller in Claude Code?

Run `npx skills add nanocoai/nanoclaw --skill learn -a claude-code`. Or copy the skill folder (.claude/skills/learn in nanocoai/nanoclaw) into .claude/skills/learn in your project. Claude Code loads it when a task matches its description.

How do I install Skill Distiller in Codex?

Run `npx skills add nanocoai/nanoclaw --skill learn -a codex`. Or copy the skill folder (.claude/skills/learn in nanocoai/nanoclaw) into .agents/skills/learn in your project. Codex loads it when a task matches its description.

Can I use Skill Distiller in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nanocoai/nanoclaw --skill learn -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/learn, .gemini/skills/learn, .github/skills/learn and .opencode/skills/learn in your project.

What does Skill Distiller need to run?

SKILL.md names no scripts, command-line tools or credentials: Skill Distiller is instructions for the agent only. Our summary lists: A project with a .claude/skills folder; Network access when the source is a URL.

Does Skill Distiller access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skill Distiller safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skill Distiller use?

Skill Distiller is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Distiller use?

About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Skill Distiller?

Skills that share tags, products or a category with Skill Distiller: Skill Creator (Azure/azqr, 794 stars), Claude Code Skill Developer Guide (diet103/claude-code-infrastructure-showcase, 10k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars) and Claude Code Command Development (anthropics/claude-plugins-official, 37k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Distiller?

nanocoai (a GitHub organization) maintains it in nanocoai/nanoclaw, which has 30,883 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on October 6, 2026.

Source: nanocoai/nanoclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.