Paw Cra Setup logo

Paw Cra Setup

Organization
pawbytes
paw-cra-setup

Sets up Pawbytes Creative Suites module in a project. Use when the user requests to 'install creative suites', 'configure creative suites', 'setup creative suites', or 'paw-cra setup'.

Overview

Publisherpawbytes
Repositoryskill-suites
Skill namepaw-cra-setup
Stars
117
Forks
20
Bundled files
4
LicenseMIT
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.

  • 4 bundled files

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

  • Open source

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

Installation

Install the Paw Cra Setup 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/pawbytes/skill-suites/tree/main/src/creative/paw-cra-setup
  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/pawbytes/skill-suites.git /tmp/skill-suites
mkdir -p .claude/skills
cp -r /tmp/skill-suites/src/creative/paw-cra-setup .claude/skills/paw-cra-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paw Cra Setup 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 Paw Cra Setup 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 Paw Cra Setup 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.

Pawbytes Creative Suites Setup

Overview

Installs and configures the Pawbytes Creative Suites module into a project. Module identity (name, code, version) comes from ./assets/module.yaml. Collects user preferences and writes them to the Pawbytes ecosystem config:

  • {project-root}/.pawbytes/config/config.yaml — shared project config: core settings at root plus a cra: section with module-specific values.
  • {project-root}/.pawbytes/config/config.user.yaml — personal settings intended to be gitignored: API keys and any variable marked user_setting: true in ./assets/module.yaml. These values live exclusively here.
  • {project-root}/.pawbytes/config/module-help.csv — registers module capabilities for the help system.

Both config scripts use an anti-zombie pattern — existing entries for this module are removed before writing fresh ones, so stale values never persist.

{project-root} is a literal token in config values — never substitute it with an actual path. It signals to the consuming LLM that the value is relative to the project root, not the skill root.

On Activation

  1. Read ./assets/module.yaml for module metadata and variable definitions (the code field cra is the module identifier)
  2. Check if {project-root}/.pawbytes/config/config.yaml exists — if a cra: section is already present, inform the user this is an update
  3. Check for existing config at {project-root}/_bmad/config.yaml (legacy BMad format). If found, inform the user that legacy config can be migrated to the new Pawbytes ecosystem format.

If the user provides arguments (e.g. accept all defaults, --headless, or inline values like user name is Alice, fal key is abc123), map any provided values to config keys, use defaults for the rest, and skip interactive prompting. Still display the full confirmation summary at the end.

Collect Configuration

Ask the user for values. Show defaults in brackets. Present all values together so the user can respond once with only the values they want to change (e.g. "change fal_key to abc123, rest are fine"). Never tell the user to "press enter" or "leave blank" — in a chat interface they must type something to respond.

Default priority (highest wins): existing config values > ./assets/module.yaml defaults.

Core config (only if no core keys exist yet): user_name (default: user), communication_language and document_output_language (default: English — ask as a single language question, both keys get the same answer). Of these, user_name and communication_language are written exclusively to config.user.yaml.

Module config: Read each variable in ./assets/module.yaml that has a prompt field. Ask using that prompt with its default value.

API Keys (stored in config.user.yaml, not committed):

  • fal_key — Required for image/video generation
  • elevenlabs_api_key — Optional, for AI voiceover
  • pexels_api_key — Optional, for stock media research

Write Files

Write a temp JSON file with the collected answers structured as {"core": {...}, "module": {...}}. Then run the config merge script:

bash
python3 ./scripts/merge-config.py --config-path "{project-root}/.pawbytes/config/config.yaml" --user-config-path "{project-root}/.pawbytes/config/config.user.yaml" --module-yaml ./assets/module.yaml --answers {temp-file}

Then register capabilities with the help CSV merge:

bash
python3 ./scripts/merge-help-csv.py --target "{project-root}/.pawbytes/config/module-help.csv" --source ./assets/module-help.csv --module-code cra

Both scripts output JSON to stdout with results. If either exits non-zero, surface the error and stop.

Create Output Directories

After writing config, create any output directories that were configured. For filesystem operations, resolve the {project-root} token and create each path:

bash
mkdir -p "{project-root}/.pawbytes/creative-suites"
mkdir -p "{project-root}/.pawbytes/creative-suites/brands"
mkdir -p "{project-root}/.pawbytes/creative-suites/knowledge"
mkdir -p "{project-root}/.pawbytes/creative-suites/daily"

Confirm

Use the script JSON output to display what was written — config values set, user settings written to config.user.yaml, help entries added, fresh install vs update. Then display the greeting from ./assets/module.yaml.

Outcome

Once the user's user_name and communication_language are known, use them consistently for the remainder of the session: address the user by their configured name and communicate in their configured language.

File Structure After Setup

{project-root}/
  .pawbytes/
    config/
      config.yaml           # Shared config (committed)
      config.user.yaml      # User settings (gitignored)
      module-help.csv       # Capability registry
    creative-suites/
      index.md              # Agency memory index
      brands/               # Brand guidelines and assets
      knowledge/            # Research and references
      daily/                # Activity logs

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 Paw Cra Setup AI skill do?

Sets up Pawbytes Creative Suites module in a project. Use when the user requests to 'install creative suites', 'configure creative suites', 'setup creative suites', or 'paw-cra setup'.

Why use Paw Cra Setup on TypingMind?

Because you install it once and use it with any model. Paw Cra Setup 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 Paw Cra Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-setup. 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 Paw Cra Setup?

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 Paw Cra Setup?

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

Is the Paw Cra Setup AI skill free?

Yes. It is published on GitHub by pawbytes 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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