Using Xskill

Organization

SkillNerds

using-xskill

Use when installing, configuring, or operating xskill (the `xskill` CLI / `pip install xskill`) — starting the daemon, registering trajectory dirs, joining a team server, understanding how trajectories become Skills, or rebuilding/re-distilling the skill library after a model change.

Overview

Publisher	SkillNerds
Repository	`xskill`
Skill name	`using-xskill`
Stars	128
Forks	26
Bundled files	3
License	MIT
Links	Skill source Repository Homepage

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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by SkillNerds on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/SkillNerds/xskill/tree/main/skills/using-xskill
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.

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/SkillNerds/xskill.git /tmp/xskill
mkdir -p .claude/skills
cp -r /tmp/xskill/skills/using-xskill .claude/skills/using-xskill

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Using Xskill 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 Using Xskill 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 Using Xskill 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.

Using xskill

Overview

xskill distills reusable Skills (SKILL.md folders) out of the real execution trajectories of coding agents (Claude Code, Codex, OpenCode, Cursor, …). A background daemon watches each agent's session logs, slices them into single-intent atoms, clusters atoms into skills, and writes/versions each skill in its own git folder. New skill versions only replace old ones when real traffic shows they serve users better (canary A/B by UX score) — not by an LLM grading itself.

Core mental model: raw trajectory → atoms → candidate routing → SKILL.md → canary A/B → installed into every agent's skill dir. You operate the daemon; the daemon does the distilling.

When to Use

Installing xskill or filling in ~/.xskill/config.yaml (LLM + embedding endpoints)
Starting/keeping the daemon running (xskill serve), or backfilling old trajectories
Joining or hosting a team server (xskill serve --server / xskill connect)
Understanding the agent pipeline, atoms, canary/UX scoring, or deployment modes
Re-distilling the whole skill library (e.g. after switching to a stronger model)

Quick Reference

Command	What it does
`pip install xskill`	Install (Python 3.9+)
`xskill serve`	Standalone daemon: FastAPI + watcher; first run writes `~/.xskill/config.yaml` then exits
`xskill serve --server`	Team server: owns all LLM calls + git; prints a join token
`xskill connect <host:port> --token <t>`	Join a team server as a thin client
`xskill registry add <path>`	Backfill / watch an extra trajectory directory
`xskill traj search <query>` / `xskill search <query>`	Search trajectories or skills
`xskill read <path> --eco <eco>`	Batch-ingest db trajectories (ngagent/opencode)
`xskill rebuild [--force]`	Re-distill from existing raw trajectories (see reference)
`xskill stats`	Token usage & estimated cost

The daemon is the engine: most commands only change state in the DB; nothing is distilled unless xskill serve (or the team server) is running.

Progressive Disclosure — read on demand

Install & configure (config.yaml fields, per-agent collect/install paths, team client setup): references/installation.md
How it works (TaskAgent → TaskClusterAgent → SkillEditAgent, atoms, canary/UX scoring, standalone vs team mode): references/mechanisms.md
Rebuild the skill library (a ready-to-run prompt that walks a model through re-distilling correctly): references/rebuilding-skill-library.md

Common Mistakes

Running rebuild with no daemon up. rebuild only resets DB state; the watcher in serve does the actual re-split/re-cluster every 30s. No daemon = nothing happens.
Deleting raw ~/.xskill/*_sessions/*.md. Those are the input to distillation — delete them and you can no longer rebuild.
Expecting DeepSeek to do embeddings. DeepSeek has no embedding endpoint; point the embedding: block at DashScope / OpenAI / Ollama.
Putting tokens in public places. Team join tokens must never land in a public repo or chat log.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Using Xskill AI skill do?

Why use Using Xskill on TypingMind?

Because you install it once and use it with any model. Using Xskill 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 Using Xskill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SkillNerds/xskill/tree/main/skills/using-xskill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Using Xskill?

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 Using Xskill?

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

Is the Using Xskill AI skill free?

Yes. It is published on GitHub by SkillNerds 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Using xskill

Overview

When to Use

Quick Reference

Progressive Disclosure — read on demand

Common Mistakes

Bundled files

Frequently asked questions

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