Skill Creator logo

Skill Creator

Organization
cubeplexai
skill-creator

Builds, edits, and publishes CubePlex skills (SKILL.md bundles) into the current workspace. Use when the user asks to create, build, write, design, package, or capture a reusable agent workflow as a skill; to edit, improve, fix, rename, or bump a skill; or to publish, upload, or share a skill in this workspace. Also use for Chinese requests like 写个 skill、封装成 skill、 发布 skill、把刚才的流程收成 skill.

Overview

Publishercubeplexai
Repositorycubeplex
Skill nameskill-creator
Stars
533
Forks
46
Bundled files
2
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 cubeplexai on GitHub. Read the source before you install it.

Installation

Install the Skill Creator 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/cubeplexai/cubeplex/tree/main/backend/skills/preinstalled/skill-creator
  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/cubeplexai/cubeplex.git /tmp/cubeplex
mkdir -p .claude/skills
cp -r /tmp/cubeplex/backend/skills/preinstalled/skill-creator .claude/skills/skill-creator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Creator 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 Skill Creator 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 Skill Creator 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.

Skill Creator

Guide for authoring a publishable skill bundle in the sandbox and installing it into the current workspace.

A skill is a directory with SKILL.md at its root plus optional sibling files. You draft under /workspace/, register with save_artifact, then publish.

When you need the full checklist or a copy-paste minimal example, read:

  • references/quality-checklist.md (use the path from load_skill for this skill)
  • references/minimal-skill.example.md

Workflow

1. Intent

Choose one:

IntentMeaning
NewDesign a skill from requirements
Capture-from-chatTurn this conversation’s workflow into a skill
Edit existingChange an installed skill and republish

2. Search before create

If the user might already have something usable, call platform_skills_find once. Only create a new skill when nothing fits or they want a custom fork.

3. Ground the request

Collect only what changes the skill: problem, audience, success criteria, out of scope. Prefer a short interview over a long questionnaire.

Capture-from-chat (required safeguards):

  1. Extract durable procedure from the conversation (steps, tools, deliverables, corrections the user made).
  2. Scrub secrets, tokens, API keys, passwords, and obvious PII. Drop one-off ticket IDs and temporary workarounds unless the user wants them kept.
  3. If the conversation is mostly credentials or customer data, refuse to package it as-is; ask for a sanitized procedure instead.
  4. Before publish, show the full draft SKILL.md (not only the description) and get explicit confirmation of that content.

4. Draft the description (before a long body)

Write frontmatter description in third person, 1–2 sentences, WHAT + WHEN, with trigger phrases the user is likely to say. Show it to the user and adjust.

Examples of good shape (fictional):

  • ✓ Drafts a short weekly status from the user's notes. Use when the user asks for a weekly status or standup write-up.
  • ✗ I can help you write status updates (first person)
  • ✗ Helps with reports (no WHEN)

5. Create the bundle directory

Somewhere under /workspace/ (recommended: /workspace/skills/<slug>/).

  • Do not draft under /tmp/ (lost on restart).
  • Do not write into /workspace/.skills/... (read-only sync of installed skills).

Typical layout:

text
/workspace/skills/weekly-status-summary/
  SKILL.md                 # required at root
  scripts/                 # optional — executable helpers
  references/              # optional — long docs loaded on demand (plural)
  templates/               # optional — fixtures the agent fills in

Directory name need not match frontmatter name, but matching helps.

6. Write SKILL.md

See Frontmatter and Body below. Optional supporting files: reference them with bundle-relative paths (e.g. python scripts/fetch.py, read references/schema.md). At runtime the agent must use the path field from load_skill for absolute paths — never hand-build /workspace/.skills/<name>/... (colons become __ on disk).

7. Pre-publish checklist

Run through references/quality-checklist.md (or the short list there). Do not publish until frontmatter, layout, size caps, and rule C pass.

8. Register as skill artifact

Call save_artifact with:

  • path = the bundle directory
  • artifact_type="skill"
  • entry_file="SKILL.md"
  • name = human-readable name (usually frontmatter name)

The conversation artifact panel shows a Publish button.

9. Publish to the current workspace

A skill artifact is a draft until published. It does not appear in load_skill or the available-skills list before that. Publish installs into the current workspace (not the org-wide admin marketplace zip path).

Ask how the user wants to publish:

  • They click Publish in the artifact panel, or
  • You call platform_skills_publish_skill(artifact_id="...") with their consent

Report the returned canonical name (e.g. acme:weekly-status-summary) and version.

10. Light verify

  1. load_skill(<canonical_name>) — confirm content and path.
  2. Optional: one cheap dry-run of the skill’s main path if the user wants proof.

Editing an existing skill

Installed skill trees under /workspace/.skills/<safe-name>/<version>/ are read-only and rewritten on every sync. Never edit in place.

  1. load_skill the skill. Use the returned path as the copy source (do not reconstruct paths; org:slug becomes org__slug on disk).
  2. Copy to a writable path, e.g. cp -r <path-from-load_skill> /workspace/skills/<slug>
  3. Edit. Leave version unset so the server assigns the next patch.
  4. save_artifact + publish (same as create), with consent.

Fork semantics (critical)

SourceWhat publish does
Uploaded org:slugNew version of that skill when name is unchanged
Preinstalled bare nameCreates/updates org-slug:<name> — a fork, not a system overwrite

Also:

  1. Tell the user clearly this is a fork if the source was preinstalled.
  2. Prefer a distinct frontmatter name for customizations so the fork does not sit next to the same bare slug. If they reuse the slug, warn that both may stay installed.
  3. Make the fork description distinguishable so auto-invoke can prefer it.
  4. Verify with load_skill on the fork’s canonical name.
  5. Do not claim that forking disables or shadows the preinstalled skill — both can remain enabled; load_skill requires the exact name.

Frontmatter

yaml
---
name: my-skill          # required — Name rules
description: …          # required — Description rules
version: 1.0.0          # optional — omit by default
keywords:               # optional
  - tag-one
---

Name rules

  • Format: ^[a-z0-9][a-z0-9-]{0,62}$ (max 63 chars)
  • No colons — the server adds the org prefix at publish time
  • Prefer short stable slugs users will say; do not force gerund forms

Description rules

Loaded into the agent’s skill list and drives auto-load. Wrong description → skill never fires.

  • Third person only
  • WHAT + WHEN + likely trigger phrases
  • One or two sentences

Version rules

  • Omit by default — server assigns next patch (1.0.0, then 1.0.1, …)
  • Same version string cannot be published twice (VersionCollisionError)
  • Set version only if the user explicitly wants a specific number

Optional env requirements

yaml
cubeplex:
  requires:
    env: [MY_API_KEY]

Only requires.env is consumed today (surfaced at preview/install). Aliases openclaw, clawdbot, clawdis behave the same as cubeplex.

Body guidelines

Second person, step by step

The body is the agent’s runbook. Numbered steps; say which tool to call and what to deliver.

One job per skill

Prefer two skills over one giant create/edit branch.

Keep it short

Loaded skill text stays in context for the rest of the conversation. Cut general programming lectures and anything already in the system prompt. Target under 500 lines; put bulk in references/, scripts/, or templates/.

Platform tools — rule C (not a catalog)

Assume the runtime agent has the same class of platform tools you see in this run (sandbox, artifacts, skills APIs, delegation, etc.). For parameters, use the live tool list / schemas in the current conversation.

Do not restate full tool schemas inside the skill. Do name a tool when this workflow depends on it: when to prefer it, and any workflow-local constraints the generic description does not already cover.

DoDon’t
Name exact tools this job needsDump every platform tool “for completeness”
Prefer/avoid rules for this deliverableCopy system-prompt tool prose wholesale
Skill-specific contracts (checklists, prompt shape for sub-tasks)Point authors at other installed skills as templates

If the skill does not need a capability, do not mention it.

External services

For MCP or HTTP APIs: exact tool name + one concrete input/output example.

Terminology and time

One term per concept. Avoid “before date X, use Y”; use a clear Legacy section or remove outdated guidance.

Size limits

Server rejects bundles with a single file > 10 MB or total size > 50 MB.

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 Skill Creator AI skill do?

Builds, edits, and publishes CubePlex skills (SKILL.md bundles) into the current workspace. Use when the user asks to create, build, write, design, package, or capture a reusable agent workflow as a skill; to edit, improve, fix, rename, or bump a skill; or to publish, upload, or share a skill in this workspace. Also use for Chinese requests like 写个 skill、封装成 skill、 发布 skill、把刚才的流程收成 skill.

Why use Skill Creator on TypingMind?

Because you install it once and use it with any model. Skill Creator 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 Skill Creator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cubeplexai/cubeplex/tree/main/backend/skills/preinstalled/skill-creator. 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 Skill Creator?

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 Skill Creator?

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

Is the Skill Creator AI skill free?

It is published on GitHub by cubeplexai. Check the repository for licensing terms. 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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