Portable Bundle Review
回答 bundle 相关问题时:
- 区分 portable DSL 资源与 Host 环境绑定。
- 说明根资源及其传递依赖,而不是把整个 Host 存储当成 bundle。
- 对缺失的 Runtime、MCP、Plugin 或 Secret 给出明确的绑定建议。
- 不建议修改 bundle 内的 portable 资源来完成本地绑定。
检查并解释 portable Pragma bundle 的内容、依赖和环境绑定。
| Publisher | pqpo |
| Repository | pragma |
| Skill name | portable-bundle-review |
| Stars | 248 |
| Forks | 15 |
| Bundled files | Instructions only |
| License | AGPL-3.0 |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by pqpo on GitHub. Read the source before you install it.
Install the Portable Bundle Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
https://github.com/pqpo/pragma/tree/main/examples/projects/bundle-transfer/skillAny agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/pqpo/pragma.git /tmp/pragma
mkdir -p .claude/skills
cp -r /tmp/pragma/examples/projects/bundle-transfer/skill .claude/skills/portable-bundle-reviewEnable Portable Bundle Review 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.
AI skills are plain Markdown instructions rather than provider-specific code, so Portable Bundle Review 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.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
回答 bundle 相关问题时:
检查并解释 portable Pragma bundle 的内容、依赖和环境绑定。
Because you install it once and use it with any model. Portable Bundle Review 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.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pqpo/pragma/tree/main/examples/projects/bundle-transfer/skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
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.
As many as you like. As long as a model supports skills, you can use Portable Bundle Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by pqpo under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.
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.
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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