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Principle Boundary Discipline

OrganizationPopular
cursor
principle-boundary-discipline

Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.

Overview

Publishercursor
Repositoryplugins
Skill nameprinciple-boundary-discipline
Stars
8K
Forks
728
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Principle Boundary Discipline 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.
  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/cursor/plugins.git /tmp/plugins
mkdir -p .claude/skills
cp -r /tmp/plugins/pstack/skills/principle-boundary-discipline .claude/skills/principle-boundary-discipline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Principle Boundary Discipline 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 Principle Boundary Discipline 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 Principle Boundary Discipline 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.

Boundary Discipline

Place validation, type narrowing, and error handling at system boundaries. Trust internal code unconditionally. Business logic lives in pure functions. The shell is thin and mechanical.

Why: Scattered validation is noisy, redundant, and gives a false sense of safety. Keep logic out of framework wiring so it can be tested without the framework.

The pattern:

  • At boundaries (CLI args, config files, external APIs, network protocols): validate, return errors, handle defensively.
  • Inside the system: typed data, error propagation, no re-validation. Trust the types.
  • Across the boundary. Expose domain concepts, not the boundary's private representation. Keep general-purpose mechanism inside and special-purpose policy at the edge.

Applications:

Validation and error handling:

  • Validate config at parse time (the boundary), not inside business logic
  • Parse raw data into domain types at the boundary
  • Do not re-export transport, storage, framework, or wire types through the public surface
  • No redundant nil checks deep in call chains if the boundary already validated

Code organization:

  • Business logic in pure functions with no framework dependencies
  • Parse functions: pure transforms from raw bytes to typed state
  • Prompt construction: structured state in, string out
  • Scoring and assessment: pure transforms from state to results

The tests:

  • "Is this data crossing a system boundary right now?" If not, validation is redundant.
  • "Can this be a pure function that the shell just calls?" If yes, extract it.

Frequently asked questions

What does the Principle Boundary Discipline AI skill do?

Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.

Why use Principle Boundary Discipline on TypingMind?

Because you install it once and use it with any model. Principle Boundary Discipline 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 Principle Boundary Discipline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cursor/plugins/tree/main/pstack/skills/principle-boundary-discipline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Principle Boundary Discipline?

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 Principle Boundary Discipline?

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

Is the Principle Boundary Discipline AI skill free?

It is published on GitHub by cursor. 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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