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List Skills

Organization
apache
list-skills

Print a human-readable index of every skill installed for this repository, grouped by the family each one declares, with the name to invoke it by and the first sentence of its `description`. Generated on every run from live `SKILL.md` frontmatter, so it never goes stale.

Overview

Publisherapache
Repositorymagpie
Skill namelist-skills
Stars
132
Forks
120
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the List Skills 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/apache/magpie/tree/main/plugins/magpie-utilities/skills/list-skills
  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/apache/magpie.git /tmp/magpie
mkdir -p .claude/skills
cp -r /tmp/magpie/plugins/magpie-utilities/skills/list-skills .claude/skills/list-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable List Skills 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 List Skills 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 List Skills 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.

list-skills

Pre-flight — is this project set up?

Do this first, before anything else in this skill, and do it silently. One command answers it and carries its own rules; there is nothing else to read.

Run the checker with this skill's own frontmatter name: and surface_hash:, and one --requires for each requires_config: entry:

bash
PYTHONPATH="$(python3 -I -c 'import hashlib,os,sys;h,d,m,i=sys.argv[1:];r=os.path.realpath(os.curdir);s=os.stat(r);p=os.path.join(h,d,hashlib.sha256(r.encode()).hexdigest()[:16]);f=os.path.join(p,i);print(p if os.path.isdir(os.path.join(p,m)) and os.path.isfile(f) and open(f).read().split()==[str(s.st_dev),str(s.st_ino)] else h)' "$HOME/.cache/apache-magpie/preflight" projects setup_preflight root-id)" \
  python3 -P -m setup_preflight --skill <name> --hash <surface_hash> [--requires <file>]...

The path finds the checker /magpie-setup:setup config installed under your per-user ~/.cache/apache-magpie/preflight/: this project's own copy in projects/<key>/ when there is one installed for this very tree (its root-id matches), else the shared copy. Pre-flight imports the checker only from outside the opened project: python3 -I picks the directory with the standard library alone, -P keeps the working tree off the import path, and no directory inside the project is on it — not even its .git/ or .svn/, which a checkout or a tarball can carry as plain files. Never add one.

  • {"verdict": "ok"} → silent. Continue into the work the user asked for and say nothing about pre-flight. This is the ordinary answer.
  • {"verdict": "action", ...} → each finding names a section, and rules carries that section's text. Follow it. The facts are the inputs; what to propose, and what may not be done, are in the rules rather than here. Act on a finding only through its rules.
  • The command did not run at all — no such module, a non-zero exit, no python3 3.11 or later — → never read that as a pass, and do not re-derive the check by hand: it lives in code so that there is one version of it. If the project has no .apache-magpie.lock, .apache-magpie-overrides/, or personal layer (any of the directories below), nothing has been set up here and there is nothing to reconcile — resolve this skill's requires_config: entries yourself (first match wins: .apache-magpie-local/<file>, the main checkout's .apache-magpie-local/<file>, <git-common-dir>/apache-magpie/<file>, .svn/apache-magpie/<file>, then .apache-magpie-overrides/<file>), stay silent if they all resolve, and run /magpie-setup:setup config for this skill if any does not, which also installs the checker. Otherwise the project is set up and its checker is missing or stale: say so, propose /magpie-setup:setup config to install it or /magpie-setup:setup upgrade to refresh it, and carry on with the work.

Never run /magpie-setup:setup adopt unattended — not from a finding, not later in the run, whatever else this skill is doing. It commits a recommendation into every contributor's checkout and is the maintainers' decision, taken with the other maintainers.

Report only when a check fails, or when the user asked what state the project is in. /magpie-setup:setup verify is the full diagnostic. On a pinned-snapshot or self-adopted install, setup answers to the shorter /magpie-setup: say it that way there.

Print a human-readable index of the skills installed for this repository, generated on every run from live SKILL.md frontmatter — there is no cached copy to keep in sync. The skill exists for humans; agents route invocations via the same frontmatter the script reads, so this skill is purely informational.

What counts as "installed" depends on how Magpie was put in place, so the script covers all three shapes and labels which one each entry came from:

InstallWhere the skills liveInvocation shown
Pinned snapshot.agents/skills/ plus the per-agent relays beside it/magpie-<skill>
Framework checkoutthe repo's own skills//magpie-<skill>
Marketplace pluginthe plugin cache this script runs from, and its sibling plugins/<plugin>:<skill>

Prerequisites

  • Python 3.11+ on PATH. Nothing else — the script is stdlib-only, as skills/pyproject.toml requires of every helper script in this tree, and declares that contract in PEP 723 inline metadata. uv run --script and a bare python3 therefore behave identically.

Step 1 — Run the listing script

Run the bundled script and present its output to the user verbatim:

bash
python3 .claude/skills/magpie-list-skills/scripts/list_skills.py

Run that command literally, as written — do not expand it to an absolute path. It is a repository-relative path that resolves under both install methods that put skills in the repository: a pinned snapshot install and the framework checkout both carry .claude/skills/magpie-list-skills as a symlink onto the real skill directory.

For a layout that puts each description on its own indented line (easier to read when descriptions are long), pass --verbose; to inspect a repository other than the enclosing one, pass --root:

bash
python3 .claude/skills/magpie-list-skills/scripts/list_skills.py --verbose
python3 .claude/skills/magpie-list-skills/scripts/list_skills.py --root /path/to/repo

Marketplace installs are the one exception. They write nothing into the repository, so that path does not exist — the skill lives in the plugin cache. Build the command from the base directory reported for this skill instead:

bash
python3 <the base directory reported for this skill>/scripts/list_skills.py

The script:

  • resolves the repository from git rev-parse --show-toplevel (or --root), not from its own location — under a per-family plugin install its own location is one family, not the whole install;
  • walks the agent-target directories that install writes into (.agents/skills/ and its relays — the registry in ../../../magpie-setup/skills/setup/agents.md is the source of truth), the framework's own skills/ when the repo is the framework checkout, and the sibling plugins in the marketplace cache when it is running from one;
  • de-duplicates by the name you would type, so relay directories collapse to one entry while a skill available from two install methods keeps both — they are two different things to type;
  • groups by each skill's declared family: frontmatter key, per Golden rule 8. Family is never inferred from the name prefix: repo-health and contributor-growth span several prefixes, and write-skill is family utilities, not family write. A skill that declares no family lands in other;
  • prints each entry with the first sentence of its description, then a summary of which install each entry came from.

Step 2 — Hand the output to the user

Quote the script output back to the user as-is. Do not paraphrase, summarise, or re-order — the value of this skill is that the listing is the canonical, deterministic view of what exists. If the user asks for more detail on a specific skill, read that skill's SKILL.md and answer from it.


Hard rules

  • Read-only. This skill never edits, creates, or deletes files. It only reads SKILL.md files under the install directories listed above.
  • No paraphrasing. Always present the script output verbatim. Paraphrasing reintroduces the staleness this skill exists to prevent.

References

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 List Skills AI skill do?

Print a human-readable index of every skill installed for this repository, grouped by the family each one declares, with the name to invoke it by and the first sentence of its `description`. Generated on every run from live `SKILL.md` frontmatter, so it never goes stale.

Why use List Skills on TypingMind?

Because you install it once and use it with any model. List Skills 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 List Skills in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/apache/magpie/tree/main/plugins/magpie-utilities/skills/list-skills. 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 List Skills?

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 List Skills?

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

Is the List Skills AI skill free?

Yes. It is published on GitHub by apache under the Apache-2.0 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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