Requirements

Community

owainlewis

requirements

Defines system product requirements: users, outcomes, capabilities, business rules, scope, and acceptance. Use for a new service or system, or a change to its product expectations.

Overview

Publisher	owainlewis
Repository	`blueprint`
Skill name	`requirements`
Stars	419
Forks	73
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by owainlewis on GitHub. Read the source before you install it.

Installation

Install the Requirements AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/owainlewis/blueprint/tree/main/skills/requirements
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.

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/owainlewis/blueprint.git /tmp/blueprint
mkdir -p .claude/skills
cp -r /tmp/blueprint/skills/requirements .claude/skills/requirements

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Requirements 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 Requirements 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 Requirements 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.

Requirements

Create or update root REQUIREMENTS.md. Describe the product, what it does, and its key features. Keep this as a long-running product document. Use /spec for one feature and /architecture for system technical decisions.

Process

Read the request, repository instructions, existing requirements, and relevant evidence. Reuse decisions already made.
Identify the users, problem, desired outcome, scope, and constraints. Separate stated needs from assumptions. Inspect the repo for facts; ask the user for missing product decisions that could change the result.
Write the requirements using the shape below. Give each requirement a stable REQ-n ID. Never reuse or renumber existing IDs.
Check that the requirements agree, cover relevant failure behavior, and can be tested. Record unresolved decisions and whether they block architecture or delivery.
Stop with the document ready for human review. Do not design the implementation, plan tasks, or write code.

Document shape

Purpose and users: the problem, who has it, and the outcome they need.
User journey: when several capabilities need connecting, show one realistic path from the problem to the desired result.
Evidence and assumptions: link supplied research, feedback, or existing behavior that supports the problem. Label consequential assumptions and how to validate them. Do not invent evidence.
Key features and scope: the main capabilities, their value, and explicit non-goals.
Requirements: observable behavior, business rules, permissions, and user-visible failure and recovery. Define domain concepts when needed.
Constraints: required compatibility, security, privacy, operational, and performance limits. Use measurable thresholds when known; mark unknown targets as open decisions.
Acceptance: observable conditions for the system capabilities. Leave detailed feature scenarios and checks to its spec.
Success measures: how to judge value after delivery, when evidence supports a measure. Keep these separate from implementation acceptance.
Open decisions: each missing answer, recommended default when justified, and its effect on further work.

Use only sections that help define this product. Combine related points and omit sections that add no useful information.

Update this document when the product, key features, scope, or business rules change. Keep it current; preserve feature decision history in specs. Keep feature implementation detail in specs.

Keep implementation choices out of requirements. Include an imposed technology only as a stated constraint. Do not invent user research, targets, or business rules.

Return

Report the path, decisions made, and any blocking question.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB

Frequently asked questions

What does the Requirements AI skill do?

Defines system product requirements: users, outcomes, capabilities, business rules, scope, and acceptance. Use for a new service or system, or a change to its product expectations.

Why use Requirements on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/owainlewis/blueprint/tree/main/skills/requirements. 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 Requirements?

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 Requirements?

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

Is the Requirements AI skill free?

Yes. It is published on GitHub by owainlewis 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Requirements

Process

Document shape

Return

Bundled files

Frequently asked questions

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