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Project Planning

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hugobowne
project-planning

Plan new software projects by decomposing the goal into MVP tasks, researching frameworks and libraries with subagents, and preferring opinionated prebuilt solutions over bespoke complexity. Use when starting a new project, scoping an idea, choosing a stack, or producing an implementation plan for a single-user MVP.

Overview

Publisherhugobowne
Repositoryshow-us-your-agent-skills
Skill nameproject-planning
Stars
70
Forks
10
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 hugobowne on GitHub. Read the source before you install it.

Installation

Install the Project Planning 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/hugobowne/show-us-your-agent-skills/tree/main/skills/project-planning
  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/hugobowne/show-us-your-agent-skills.git /tmp/show-us-your-agent-skills
mkdir -p .claude/skills
cp -r /tmp/show-us-your-agent-skills/skills/project-planning .claude/skills/project-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Planning 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 Project Planning 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 Project Planning 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.

Project Planning

Use this skill to turn a fresh project idea into a focused, MVP-first plan that favors prebuilt solutions and opinionated frameworks over custom complexity.

Workflow

  1. Read references/project-planning.md.
  2. Clarify the goal in one sentence and define the single-user MVP boundary: what ships in the first cut, what is explicitly out of scope.
  3. Decompose the goal into a small set of manageable tasks. Group by user-visible outcome, not by layer.
  4. Spawn subagents in parallel to research frameworks and libraries that could absorb whole tasks. Prefer pre-built solutions unless a clear constraint rules them out.
  5. Start from an official scaffold or starter via bunx create-* (bunx create-next-app, bunx create-vite, bunx create-t3-app, bunx create-tanstack, bunx create-expo) instead of hand-rolling the project skeleton.
  6. Before any dependency install in the new project, create or preserve bunfig.toml with [install] minimumReleaseAge = 259200. Prefer scaffold flags that skip the initial install, then run bun install.
  7. Pick an opinionated framework (e.g. Next.js, TanStack Start) when it improves organization and removes wiring decisions. Skip framework-grade tooling for one-screen utilities. Ask the user which framework to use if unclear.
  8. For UI, initialize shadcn/ui with bunx shadcn@latest init and choose a minimalist preset - prefer shadcn blocks, you can ask the user to pick. Pull in components on demand, not preemptively.
  9. Lay out components and services in a logical, opinionated structure before any code is written.
  10. Decide the minimum useful testing surface and the minimum useful git-hook surface. Both default to small.
  11. Produce a short plan: goal, MVP scope, task list, stack choices with one-line rationale, deferred items.

Planning Rules

  • Build for one user first.
  • Use Bun as the runtime, package manager, and script runner by default.
  • Start every new project from an official scaffold or template, invoked through bunx create-* (e.g. bunx create-next-app, bunx create-vite, bunx create-t3-app, bunx create-tanstack, bunx create-expo).
  • Every Bun project must include a root bunfig.toml with minimumReleaseAge = 259200 under [install] before bun install or bun add resolves new packages.
  • For UI, default to shadcn/ui with a minimalist preset. Add components with bunx shadcn@latest add <component> as they are actually needed.
  • Prefer prebuilt over bespoke. Reach for a library, hosted service, or framework primitive before writing your own.
  • Choose boring, well-documented defaults. Novelty is a cost, not a feature.
  • Cut features before cutting clarity. If the MVP is too big, remove scope, do not compress the design.
  • Pick one opinionated framework per project. Do not mix two routing or data layers.
  • Organize by feature or domain, not by file type, once there is more than one screen.
  • Write tests for critical logic and infrastructure: money, auth, data integrity, deploy paths. Skip tests for trivial glue and UI that will churn.
  • Use git hooks for formatting and fast static checks. Do not run full test suites or type-checks on every commit.
  • Defer anything that is not on the path to a working MVP: analytics, feature flags, advanced error reporting, premature abstractions.
  • Re-evaluate the plan once the first end-to-end slice runs. Replan from evidence, not from the original guess.

Subagent Use

  • Launch independent research subagents in parallel: one per framework or library question.
  • Give each subagent a self-contained brief: the problem, constraints, what a good answer looks like, and a length cap.
  • Ask for a recommendation plus the main tradeoff, not a survey of every option.
  • Do not delegate the final decision. Synthesize subagent findings yourself before committing to a stack.

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 Project Planning AI skill do?

Plan new software projects by decomposing the goal into MVP tasks, researching frameworks and libraries with subagents, and preferring opinionated prebuilt solutions over bespoke complexity. Use when starting a new project, scoping an idea, choosing a stack, or producing an implementation plan for a single-user MVP.

Why use Project Planning on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hugobowne/show-us-your-agent-skills/tree/main/skills/project-planning. 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 Project Planning?

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 Project Planning?

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

Is the Project Planning AI skill free?

Yes. It is published on GitHub by hugobowne 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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