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Vibe Coding Workflow

Community
MaxStudiocoder
vibe-coding-workflow

Run a document-driven Vibe Coding workflow for complex AI-assisted software projects. Use when the user wants to build or refactor a non-trivial project with Codex, Claude Code, Cursor, or another coding agent; asks for vibe coding; wants requirements, design docs, task decomposition, multi-agent implementation, progress tracking, or verification loops; or needs to turn a rough product idea into an executable engineering plan.

Overview

PublisherMaxStudiocoder
Repositoryvibe-coding-workflow
Skill namevibe-coding-workflow
Stars
50
Forks
6
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Vibe Coding Workflow 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/MaxStudiocoder/vibe-coding-workflow/tree/main/vibe-coding-workflow
  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/MaxStudiocoder/vibe-coding-workflow.git /tmp/vibe-coding-workflow
mkdir -p .claude/skills
cp -r /tmp/vibe-coding-workflow/vibe-coding-workflow .claude/skills/vibe-coding-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vibe Coding Workflow 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 Vibe Coding Workflow 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 Vibe Coding Workflow 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.

Vibe Coding Workflow

Use this skill to turn a vague or complex coding goal into a controlled engineering workflow: requirements, design, task split, implementation, and verification. Prefer this workflow when a single prompt would create too much ambiguity, context pressure, or unreviewable code.

Core Rules

  • Do not start implementation until the goal, scope, and success criteria are clear enough to test.
  • Keep project knowledge in files, not only in chat. Use doc/ for planning artifacts and update existing project state files when present.
  • Make every phase produce an artifact that the next phase consumes.
  • Keep tasks small enough for one agent pass. A task should have explicit files, steps, and checks.
  • Treat AI output as a draft until verified with diffs, tests, lint, type checks, and runtime checks.
  • Pause and ask the user when a requirement, product decision, data contract, destructive action, or external dependency is unclear.

Workflow

1. Stabilize The Project

Inspect the repository before planning. Identify the language, framework, package manager, test commands, lint commands, and existing conventions. If the project is new, choose conservative defaults and prefer tooling the user already knows.

For Python projects, prefer uv when no project-specific tool is established. Use it for virtual environment, dependency, and command management.

Create planning directories only when needed:

text
doc/
  proposal.md
  high-level-design.md
  detailed-design.md
  prompt.md
  tasks/
    progress.md

2. Clarify Requirements

Interview the user or the existing codebase before writing code. Convert rough intent into doc/proposal.md.

Include:

  • Goal and non-goals
  • Target users or runtime context
  • Inputs, outputs, and external dependencies
  • Functional requirements
  • Constraints and assumptions
  • Success criteria and acceptance checks
  • Open questions

If important answers are missing, ask targeted questions before moving to design.

3. Design Before Implementation

Generate or update:

  • doc/high-level-design.md for architecture, modules, data flow, storage, dependencies, and major tradeoffs.
  • doc/detailed-design.md for module responsibilities, interfaces, file layout, algorithms, errors, tests, and edge cases.

Require the design to call out risk, ambiguity, and alternatives. Do not hide uncertainty in confident prose.

4. Split Tasks

Break doc/detailed-design.md into independent task files:

text
doc/tasks/<module-or-feature>.md
doc/tasks/progress.md

Each task file must include:

  • Objective
  • Input docs
  • Files expected to change
  • Implementation steps
  • Tests and checks
  • Definition of done
  • Dependencies on other tasks

progress.md must be the shared source of truth. Use checklists for task state and keep notes short.

5. Generate The Control Prompt

When the project is ready for agentic implementation, generate doc/prompt.md. It should define:

  • Main agent role: coordinate, track progress, review diffs, run checks, update progress.md.
  • Sub-agent role: implement exactly one task or module, add tests, report blockers, update task status.
  • Required context files: proposal, designs, task files, progress.
  • Guardrails: ask on ambiguity, avoid unrelated refactors, do not skip tests, do not overwrite user work.
  • Verification commands and final reporting format.

Load detailed templates from references/prompt-templates.md when drafting prompts or planning docs.

6. Implement In Small Passes

Work from doc/tasks/progress.md, one task or tightly related group at a time. Before edits, inspect the relevant files and confirm the task still matches the codebase.

For each implementation pass:

  1. Select the next unblocked task.
  2. Read the task file and dependent design sections.
  3. Implement only the scoped change.
  4. Add or update focused tests.
  5. Run the task's checks.
  6. Inspect git diff.
  7. Update progress.md with status, commands run, failures, and next steps.

Use sub-agents only when the task boundaries are clean enough that their work can be reviewed independently.

7. Verify And Close

Before calling the work done:

  • Run the relevant test suite.
  • Run lint and type checks when available.
  • Run a smoke test or dev server for user-facing behavior when applicable.
  • Inspect the final diff for unrelated edits, generated clutter, secrets, and accidental rewrites.
  • Update project state or session logs when the session produced durable context.
  • Report what changed, what was verified, and remaining risks.

Templates

Use references/prompt-templates.md for reusable prompts and document skeletons:

  • Requirements discussion prompt
  • Proposal template
  • High-level design template
  • Detailed design template
  • Task file template
  • Progress file template
  • Main-agent prompt
  • Sub-agent prompt
  • Verification checklist

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 Vibe Coding Workflow AI skill do?

Run a document-driven Vibe Coding workflow for complex AI-assisted software projects. Use when the user wants to build or refactor a non-trivial project with Codex, Claude Code, Cursor, or another coding agent; asks for vibe coding; wants requirements, design docs, task decomposition, multi-agent implementation, progress tracking, or verification loops; or needs to turn a rough product idea into an executable engineering plan.

Why use Vibe Coding Workflow on TypingMind?

Because you install it once and use it with any model. Vibe Coding Workflow 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 Vibe Coding Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MaxStudiocoder/vibe-coding-workflow/tree/main/vibe-coding-workflow. 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 Vibe Coding Workflow?

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 Vibe Coding Workflow?

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

Is the Vibe Coding Workflow AI skill free?

Yes. It is published on GitHub by MaxStudiocoder 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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