Nw Collaboration And Handoffs

Organization

nWave-ai

nw-collaboration-and-handoffs

Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows

Overview

Publisher	nWave-ai
Repository	`nWave`
Skill name	`nw-collaboration-and-handoffs`
Stars	616
Forks	65
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by nWave-ai on GitHub. Read the source before you install it.

Installation

Install the Nw Collaboration And Handoffs AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-collaboration-and-handoffs
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.

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/nWave-ai/nWave.git /tmp/nWave
mkdir -p .claude/skills
cp -r /tmp/nWave/nWave/skills/nw-collaboration-and-handoffs .claude/skills/nw-collaboration-and-handoffs

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Collaboration And Handoffs 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 Nw Collaboration And Handoffs 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 Nw Collaboration And Handoffs 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.

Collaboration and Handoffs

Cross-Agent Collaboration

Receives From

acceptance_designer (DISTILL): E2E acceptance tests | business validation requirements | production integration patterns
solution_architect (DESIGN): architecture patterns | component boundaries | technology constraints | port definitions

Hands Off To

feature_completion_coordinator (DELIVER): working implementation | complete test coverage | quality metrics | refactored codebase | validated business value

Collaborates With

architecture_diagram_manager: visual validation of implementation against architecture | diagram updates during refactoring

4 Workflow Handoff Patterns

1. TDD to Mikado

Trigger: complex architectural refactoring requirements emerge during TDD
Content: working implementation with test coverage | identified architectural complexity | business value articulation
Transition: Pause TDD at stable green state -> Activate Mikado exploration -> Define business-value-focused refactoring goal -> Execute exhaustive exploration with discovery-tracking commits -> Build complete dependency tree -> Resume through Mikado execution or transition to refactoring

2. TDD to Refactoring

Trigger: feature implementation complete, code quality improvements needed
Content: working implementation with test coverage | code smells identified | all tests passing
Transition: Commit TDD implementation (all tests green) -> Activate progressive refactoring -> Execute comprehensive code smell detection -> Apply Level 1-6 refactoring in mandatory sequence -> Maintain 100% test pass rate throughout -> Commit after each successful atomic transformation

3. Mikado to Systematic Execution

Trigger: Mikado exploration complete, true leaves identified
Content: complete dependency tree with annotations | true leaves with zero prerequisites | refactoring mechanics per node
Transition: Validate exploration completeness -> Confirm tree structure with proper nesting -> Activate systematic execution -> Execute leaves bottom-up using embedded refactoring knowledge -> Maintain shared progress tracking -> Ensure test-driven safety throughout

4. Integrated Workflow Patterns

yaml
tdd_with_continuous_refactoring:
  pattern: "TDD -> L1-L2 Refactoring -> TDD (continuous cycle)"
  timing: "After each GREEN phase in inner TDD loop"
  scope: "Level 1-2 only during active TDD"

tdd_with_mikado_planning:
  pattern: "TDD -> Mikado Exploration -> TDD Continuation"
  timing: "When architectural complexity blocks TDD progress"
  scope: "Full Mikado Method with return to TDD"

mikado_with_systematic_execution:
  pattern: "Mikado Exploration -> Systematic Refactoring Execution"
  timing: "After exploration identifies true leaves"
  scope: "Full systematic refactoring with tree-guided execution"

4 Commit Message Formats

1. TDD Implementation


feat(<component>): <business-value-description>

- Implemented: <specific feature or capability>
- Tests: <test coverage details>
- Architecture: <architectural layer(s) touched>
- E2E Status: <enabled/disabled with reason>

2. Mikado Discovery


Discovery: [SpecificClass.Method(parameters)] requires [ExactPrerequisite] in [FilePath:LineNumber]

- Tree: docs/mikado/<goal-name>.mikado.md updated
- Dependencies: <count> new dependencies discovered
- Exploration: <status of exploration phase>

3. Mikado Implementation


feat(mikado): Implement leaf node - <node-description>

- Mikado Node: <specific node from tree>
- Tree Progress: <completed-count>/<total-count> leaves complete
- Tests: All passing

4. Refactoring Transformation


refactor(level-N): <atomic-transformation-description>

- Applied: <specific refactoring technique>
- Target: <code smell(s) addressed>
- Files: <list of modified files>
- Tests: All passing
- Mikado: <mikado-node-reference> (when applicable)

Frequently asked questions

What does the Nw Collaboration And Handoffs AI skill do?

Cross-agent collaboration protocols, workflow handoff patterns, and commit message formats for TDD/Mikado/refactoring workflows

Why use Nw Collaboration And Handoffs on TypingMind?

Because you install it once and use it with any model. Nw Collaboration And Handoffs 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 Nw Collaboration And Handoffs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-collaboration-and-handoffs. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nw Collaboration And Handoffs?

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 Nw Collaboration And Handoffs?

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

Is the Nw Collaboration And Handoffs AI skill free?

Yes. It is published on GitHub by nWave-ai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Collaboration and Handoffs

Cross-Agent Collaboration

Receives From

Hands Off To

Collaborates With

4 Workflow Handoff Patterns

1. TDD to Mikado

2. TDD to Refactoring

3. Mikado to Systematic Execution

4. Integrated Workflow Patterns

4 Commit Message Formats

1. TDD Implementation

2. Mikado Discovery

3. Mikado Implementation

4. Refactoring Transformation

Frequently asked questions

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