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Project Maintenance

Organization
VectorSpaceLab
project-maintenance

Guides in-place enhancement, extraction, and version upgrades for projects generated by Agent Starter Pack.

Overview

PublisherVectorSpaceLab
RepositoryAREX-Skill
Skill nameproject-maintenance
Stars
341
Forks
26
Bundled files
2
LicenseApache-2.0
Links
Skill sourceRepository
  • 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 VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Project Maintenance 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/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/agent-starter-pack/sub-skills/project-maintenance
  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/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/skills/repositories/repo-skills/agent-starter-pack/sub-skills/project-maintenance .claude/skills/project-maintenance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Maintenance 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 Project Maintenance 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 Project Maintenance 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.

Project maintenance

Use this sub-skill when the user already has an Agent Starter Pack project and wants to modify, shrink, or upgrade it.

Covers

  • enhance for templating Agent Starter Pack capabilities into an existing project.
  • extract for turning a scaffolded project into a minimal shareable agent.
  • upgrade for merging a generated project forward to a newer ASP version.
  • Backup, version-lock, language-detection, metadata, and 3-way merge behavior that make those workflows safe.

Excludes

  • Choosing a template for a brand-new project belongs in project-scaffolding.
  • CI/CD provisioning, deployment, and Gemini Enterprise registration belong in deployment-ops.

Read first

  • ../../references/cli-reference.md for command ownership.
  • ../../references/package-overview.md for install and sanity-check guidance.
  • references/workflows.md for the enhancement, extraction, and upgrade flows.
  • references/troubleshooting.md for backup, merge, metadata, and version-lock failures.

Common workflow

  1. Determine whether the user is enhancing, extracting, or upgrading.
  2. Check the project metadata and current layout before changing anything.
  3. Use backups or dry-run modes when available.
  4. Prefer the merge logic already built into the package rather than inventing a custom file strategy.
  5. Hand off cloud-deployment questions to deployment-ops after the local project state is correct.

Useful signals

  • enhance, --base-template, --agent-directory, --dry-run, --prefer-new, --force
  • extract, --source, --force, --dry-run
  • upgrade, asp_version, --dry-run, --auto-approve
  • backup, conflict, merge, metadata, or version-lock language

Validation mindset

  • Do not assume every generated project uses the same language or directory layout.
  • Treat missing metadata or version markers as a workflow problem that needs the maintenance reference, not as a template-selection issue.
  • If the user only needs to understand the generated project’s deployment commands, route to deployment-ops.

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 Project Maintenance AI skill do?

Guides in-place enhancement, extraction, and version upgrades for projects generated by Agent Starter Pack.

Why use Project Maintenance on TypingMind?

Because you install it once and use it with any model. Project Maintenance 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 Project Maintenance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/agent-starter-pack/sub-skills/project-maintenance. 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 Project Maintenance?

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 Project Maintenance?

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

Is the Project Maintenance AI skill free?

Yes. It is published on GitHub by VectorSpaceLab 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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