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Workflow Orchestration

Community
vxcozy
workflow-orchestration

Disciplined task execution with planning, verification, and self-improvement loops. Use when starting non-trivial tasks (3+ steps), fixing bugs, building features, refactoring code, or when rigorous execution with quality gates is needed. Includes subagent delegation, lessons tracking, and staff-engineer-level verification.

Overview

Publishervxcozy
Repositoryworkflow-orchestration
Skill nameworkflow-orchestration
Stars
118
Forks
12
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Workflow Orchestration 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/vxcozy/workflow-orchestration/tree/main
  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/vxcozy/workflow-orchestration.git \
  .claude/skills/workflow-orchestration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Workflow Orchestration 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 Workflow Orchestration 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 Workflow Orchestration 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.

Workflow Orchestration

Apply these practices for disciplined, high-quality task execution.

Quick Reference

PracticeWhen to Apply
Plan ModeAny task with 3+ steps or architectural decisions
SubagentsResearch, exploration, parallel analysis
LessonsAfter ANY user correction
VerificationBefore marking any task complete
Elegance CheckNon-trivial changes only

1. Plan Mode Default

  • Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
  • If something goes sideways, STOP and re-plan immediately
  • Use plan mode for verification steps, not just building
  • Write detailed specs upfront to reduce ambiguity

2. Subagent Strategy

Keep the main context window clean:

  • Offload research, exploration, and parallel analysis to subagents
  • For complex problems, throw more compute at it via subagents
  • One task per subagent for focused execution

Template:

Agent({
  description: "Search auth patterns",
  prompt: "Find all authentication middleware in src/ and list file paths with a one-line summary of each."
})

3. Self-Improvement Loop

After ANY correction from the user:

  1. Update tasks/lessons.md with the pattern
  2. Write rules that prevent the same mistake
  3. Review lessons at session start

Inline example (full template in references/lessons-format.md):

markdown
## 2024-01-10 - Testing
**Mistake**: Mocks hid real API behavior; production broke
**Pattern**: Over-mocking created false confidence
**Rule**: Include at least one integration test hitting real services
**Applied**: All API endpoints, external service integrations

4. Verification Before Done

  • Never mark a task complete without proving it works
  • Diff behavior between main and your changes when relevant
  • Ask yourself: "Would a staff engineer approve this?"
  • Run tests, check logs, demonstrate corrections
  • If verification fails → return to the plan step and revise before retrying

5. Demand Elegance (Balanced)

  • For non-trivial changes: pause and ask "is there a more elegant way?"
  • If a fix feels hacky: "Knowing everything I know now, implement the elegant solution"
  • Skip this for simple, obvious fixes—don't over-engineer

6. Autonomous Bug Fixing

  • When given a bug report: Just fix it. Don't ask for hand-holding
  • Point at logs, errors, failing tests—then resolve them
  • Zero context switching required from the user

Task Management Protocol

  1. Plan First: Write plan to tasks/todo.md with checkable items
  2. Verify Plan: Check in before starting implementation
  3. Track Progress: Mark items complete as you go
  4. Explain Changes: High-level summary at each step
  5. Verify Results: Run tests and confirm behavior before marking done
  6. Handle Failures: If verification fails → re-plan (step 1), don't push through
  7. Document Results: Add review to tasks/todo.md
  8. Capture Lessons: Update tasks/lessons.md after corrections

Inline example (full templates in references/task-templates.md):

markdown
# Task: Fix memory leak in WebSocket handler
## Plan
- [ ] Reproduce the issue locally
- [ ] Identify leak source with profiler
- [ ] Implement fix
- [ ] Verification: Memory stable over 1000 connections

Core Principles

  • Simplicity First: Make every change as simple as possible
  • No Laziness: Find root causes. No temporary fixes. Senior developer standards
  • Minimal Impact: Only touch what's necessary. Avoid introducing bugs

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 Workflow Orchestration AI skill do?

Disciplined task execution with planning, verification, and self-improvement loops. Use when starting non-trivial tasks (3+ steps), fixing bugs, building features, refactoring code, or when rigorous execution with quality gates is needed. Includes subagent delegation, lessons tracking, and staff-engineer-level verification.

Why use Workflow Orchestration on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vxcozy/workflow-orchestration/tree/main. 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 Workflow Orchestration?

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 Workflow Orchestration?

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

Is the Workflow Orchestration AI skill free?

Yes. It is published on GitHub by vxcozy 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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