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Dev Requirements

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codeaholicguy
dev-requirements

AI DevKit · Requirements phase guidance for starting features and reviewing requirements. Use when the user wants to capture a new requirement, clarify product scope, initialize feature docs, review requirements, or run dev-lifecycle phases 1-2.

Overview

Publishercodeaholicguy
Repositoryai-devkit
Skill namedev-requirements
Stars
1.6K
Forks
252
Bundled files
1
LicenseApache-2.0
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.

  • 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 codeaholicguy on GitHub. Read the source before you install it.

Installation

Install the Dev Requirements 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/codeaholicguy/ai-devkit.git /tmp/ai-devkit
mkdir -p .claude/skills
cp -r /tmp/ai-devkit/skills/dev-requirements .claude/skills/dev-requirements
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dev 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 Dev 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 Dev 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.

Dev Requirements

Run the requirements phases for configured AI docs features. Before making docs or code changes, propose the concrete plan for this phase and wait for user approval unless the user already approved the exact phase plan.

Phase Contract

  1. Run npx ai-devkit@latest lint before phase work.
  2. If working on a named feature, run npx ai-devkit@latest lint --feature <name>.
  3. If lint fails because project docs are not initialized, run npx ai-devkit@latest init -a -e claude --built-in --yes, then rerun lint.
  4. Read existing configured AI docs and keep diffs minimal. Do not assume docs/ai; it is only the default docs directory.
  5. Ask until every material product, UX, architecture, scope, validation, rollout, contradiction, trade-off, or open question is answered, explicitly deferred, or accepted as a named assumption.
  6. Ask one decision at a time, with why it matters, 2-3 viable options when useful, and a recommended answer.
  7. Do not create, update, approve, or transition past requirements while material open questions remain.
  8. Restate the shared understanding before updating docs or suggesting the next phase.
  9. If parent dev-lifecycle established usable task tracing, emit requirements phase, clarification/progress, blocker/open-question, and next-step events per task.

New Requirement

Use for Phase 1 or /new-requirement.

  1. Search AI DevKit memory for relevant past features or conventions with npx ai-devkit@latest memory search --query "<feature/topic>". If unfamiliar, check the memory skill first.
  2. Clarify feature name in kebab-case, problem, target users, key user stories, scope, non-goals, success criteria, UX, constraints, rollout, and validation.
  3. Brainstorm alternatives to confirm this is the right thing to build. Present 2-3 approaches with one-line trade-offs and a recommendation.
  4. Store reusable answers after clarification.
  5. Use dev-worktree to create or resume the active feature workspace with normalized <name>.
  6. Initialize docs with npx ai-devkit@latest docs init-feature <name> from the active worktree/repository and fill the returned paths. Treat those returned paths as authoritative because paths.docs may customize the docs directory.
  7. Fill requirements doc: problem statement, goals/non-goals, user stories, success criteria, constraints, open questions.
  8. Fill design doc: architecture with mermaid diagram, data models, APIs, components, design decisions, security/performance.
  9. Fill testing doc: derive scenarios from requirements success criteria and design components/edge cases as - [ ] checkboxes, plus mocks/fixtures and coverage target.
  10. If task tracing is available, record draft progress and next review step per task.
  11. Use dev-planning to create the initial task plan from the requirements, design, and testing docs.

Next: dev-requirements review, then dev-design.

Review Requirements

Use for Phase 2.

  1. Run npx ai-devkit@latest lint --feature <name> and review the requirements doc path it validates. If manual path resolution is unavoidable, first resolve .ai-devkit.json paths.docs, falling back to docs/ai.
  2. Check it against the README.md template.
  3. Search memory for relevant conventions or past patterns.
  4. Review each section: problem statement, goals/non-goals, success criteria, user stories, constraints, open questions, template compliance.
  5. Resolve every gap, contradiction, ambiguity, open question, or implicit assumption.
  6. Brainstorm alternatives for key decisions and trade-offs before accepting the first approach.
  7. Update the requirements doc with clarified answers and chosen options.
  8. Store reusable clarifications in memory.
  9. If task tracing is available, record validation progress, next step, or blockers per task.
  10. Summarize what was validated, what was updated, and remaining open items.

Next: dev-design. If fundamental gaps remain unresolvable, return to New Requirement.

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 Dev Requirements AI skill do?

AI DevKit · Requirements phase guidance for starting features and reviewing requirements. Use when the user wants to capture a new requirement, clarify product scope, initialize feature docs, review requirements, or run dev-lifecycle phases 1-2.

Why use Dev Requirements on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codeaholicguy/ai-devkit/tree/main/skills/dev-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 Dev 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 Dev Requirements?

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

Is the Dev Requirements AI skill free?

Yes. It is published on GitHub by codeaholicguy 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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