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Project Workflow

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waynesutton
project-workflow

Runs multi step work the way a careful senior engineer would. Triage before code, a short PRD in prds/, task.md kept current, docs synced after, and lessons recorded when a mistake repeats. Use when a task spans several files or steps, changes architecture, needs a plan the user can review, or when the user says "write a PRD", "plan this", "track this in task.md", or "what did we learn".

Overview

Publisherwaynesutton
Repositorybuilder-skills
Skill nameproject-workflow
Stars
405
Forks
33
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

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

Installation

Install the Project 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/waynesutton/builder-skills/tree/main/skills/project-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/waynesutton/builder-skills.git /tmp/builder-skills
mkdir -p .claude/skills
cp -r /tmp/builder-skills/skills/project-workflow .claude/skills/project-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project 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 Project 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 Project 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.

Project workflow

One loop for any task bigger than a typo. Plan in a PRD, track in task.md, sync docs when done, write down what went wrong so it does not repeat.

Skip this for one file fixes. A typo, a copy change, a single obvious bug. Just fix those.

The loop

  1. Triage. Read the request and the code before touching anything.
  2. PRD. Write prds/<slug>.md from the template. Share it if the plan has a real choice in it.
  3. Track. Add the work to task.md under ## To Do. Move items as they land.
  4. Build. Small commits worth of change at a time. Verify each step.
  5. Sync docs. Hand off to the project-docs skill to update task.md, changelog.md, files.md.
  6. Learn. If the user corrected the same thing twice, add a line to prds/lessons.md.

Triage

Before writing code, answer these in a few lines:

  • What is missing, broken, or incomplete?
  • What are two or three likely causes or approaches?
  • Which one is most likely, and why?
  • What is still unclear enough to ask about?

If the last answer is not empty, ask. One question, not five. Then wait.

For bugs, name the root cause before proposing the fix. A fix without a root cause is a guess.

PRD

Create prds/<feature-or-problem-slug>.md before non trivial work. Use the layout in references/prd-template.md.

Required sections:

  • Problem (one paragraph)
  • Root cause (bugs only)
  • Proposed solution
  • Files to change
  • Edge cases
  • Verification steps
  • Task completion log

Metadata at the top, always in UTC:

Created: YYYY-MM-DD HH:mm UTC
Last Updated: YYYY-MM-DD HH:mm UTC
Status: Draft | In Progress | Done

Keep it short. A PRD that takes longer to write than the change did is too long. Two screens is plenty for most work.

PRDs are .md files and live in prds/. Old or sensitive PRDs move to prds/archive/.

Task tracking

task.md has three sections: ## To Do, ## In Progress, ## Completed.

  • New work goes under To Do with a link to its PRD.
  • Only one item In Progress at a time when possible.
  • An item moves to Completed after verification, not after the edit.
  • Completed entries carry a YYYY-MM-DD HH:mm UTC timestamp, the files touched, and the verification command or outcome.

Good entry:

- [x] 2026-09-15 18:40 UTC Fix duplicate heartbeat writes. prds/heartbeat-dedup.md. convex/stats.ts, src/hooks/usePageTracking.ts. Verified: npx convex dev clean, no OCC retries in dashboard for 10 min.

Bad entry:

- [x] fixed heartbeat

Docs sync

After each feature or fix, task.md, changelog.md, and files.md have to agree with the code. Load the project-docs skill for the rules. In short:

  • changelog.md follows Keep a Changelog. Dates come from git log --date=short, never from memory.
  • files.md gets new files added and stale descriptions fixed.
  • Claims about what shipped come from the diff, not from the plan.

Execution style

  • Keep the change set tight. The request sets the scope. Extra ideas go in the summary, not the diff. Load avoid-feature-creep if scope starts to drift.
  • One subagent per research question when the task is large enough to benefit. Do not parallelize edits to the same file.
  • Stop and re plan if the work stops making sense. Update the PRD, then continue.
  • Before calling it done, ask: would a staff engineer approve this diff as is?

Learning loop

prds/lessons.md is a flat list. One line per lesson, newest at the bottom:

- 2026-09-15 Do not add `returns` validators that duplicate the schema doc shape; use a shared validator constant instead.

Add a lesson when:

  • the user corrects the same pattern a second time
  • a verification step catches something the plan missed
  • a tool or API behaved differently from the docs

Read prds/lessons.md at the start of any session in that repo.

Never

  • Deploy, publish, commit, or push. The user does those.
  • Mark a task done without running the verification step written in the PRD.
  • Invent a date. Run git log or use the current UTC time.
  • Write a PRD for a one line change.

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 Workflow AI skill do?

Runs multi step work the way a careful senior engineer would. Triage before code, a short PRD in prds/, task.md kept current, docs synced after, and lessons recorded when a mistake repeats. Use when a task spans several files or steps, changes architecture, needs a plan the user can review, or when the user says "write a PRD", "plan this", "track this in task.md", or "what did we learn".

Why use Project Workflow on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/waynesutton/builder-skills/tree/main/skills/project-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 Project 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 Project Workflow?

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

Is the Project Workflow AI skill free?

Yes. It is published on GitHub by waynesutton 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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