Nw Discovery Workflow logo

Nw Discovery Workflow

Organization
nWave-ai
nw-discovery-workflow

4-phase discovery workflow with decision gates, phase transitions, success metrics, and state tracking

Overview

PublishernWave-ai
RepositorynWave
Skill namenw-discovery-workflow
Stars
616
Forks
65
Bundled files
Instructions only
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.

  • 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 Discovery 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/nWave-ai/nWave/tree/main/nWave/skills/nw-discovery-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/nWave-ai/nWave.git /tmp/nWave
mkdir -p .claude/skills
cp -r /tmp/nWave/nWave/skills/nw-discovery-workflow .claude/skills/nw-discovery-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Discovery 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 Nw Discovery 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 Nw Discovery 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.

Discovery Workflow

4-Phase Overview

PHASE 1              PHASE 2              PHASE 3              PHASE 4
Problem Validation   Opportunity Mapping  Solution Testing     Market Viability
      |                    |                    |                    |
      v                    v                    v                    v
"Is this real?"      "Which matters?"     "Does it work?"      "Viable business?"

Phase Details

Phase 1: Problem Validation

Duration: 1-2 weeks | Min interviews: 5 | Techniques: Mom Test, Job Mapping Core question: Is this a real problem worth solving?

Phase 2: Opportunity Mapping

Duration: 1-2 weeks | Min interviews: 10 cumulative | Techniques: OST, Opportunity Algorithm Core question: Which problems matter most?

Phase 3: Solution Testing

Duration: 2-4 weeks | Min interviews: 5 per iteration | Techniques: hypothesis testing, prototypes Core question: Does our solution actually work?

Phase 4: Market Viability

Duration: 2-4 weeks | Min interviews: 5 + stakeholders | Techniques: Lean Canvas, 4 Big Risks Core question: Can we build a viable business?

Decision Gates

G1: Problem to Opportunity

Proceed: 5+ confirm pain + willingness to pay | Pivot: problem differs from expected | Kill: <20% confirm

G2: Opportunity to Solution

Proceed: top 2-3 score >8 (max 20) | Pivot: new opportunities discovered | Kill: all low-value Scoring: Score = Importance + Max(0, Importance - Satisfaction). Each 1-10. >8 = high importance with satisfaction gap.

G3: Solution to Viability

Proceed: >80% task completion, usability validated | Pivot: needs refinement | Kill: fundamental blocks

G4: Viability to Build

Proceed: all 4 risks addressed, model validated | Pivot: model needs adjustment | Kill: no viable model

Success Metrics

Phase 1: Problem Validation

MetricTarget
Problem confirmation>60% (3+ of 5)
FrequencyWeekly+
Current spending>$0 on workarounds
Emotional intensityFrustration evident

Done when: 5+ interviews, >60% confirmation, articulated in customer words, 3+ examples. Threshold: 60% aligns with Mom Test -- 3/5 consistent signals = proceed, <20% = kill. Combined with qualitative markers.

Phase 2: Opportunity Mapping

MetricTarget
Opportunities identified5+ distinct
Top scores>8 / max 20
Job step coverage80%+
Strategic alignmentStakeholder confirmed

Done when: OST complete, top 2-3 prioritized, team aligned.

Phase 3: Solution Testing

MetricTarget
Task completion>80%
Value perception>70% "would use/buy"
Comprehension<10 sec to understand
Key assumptions validated>80% proven

Done when: 5+ users per iteration, core flow usable, value + feasibility confirmed.

Phase 4: Market Viability

MetricTarget
Four big risksAll green/yellow
Channel validated1+ viable
Unit economicsLTV > 3x CAC (estimated)
Stakeholder signoffLegal, finance, ops

Done when: Lean Canvas complete, all risks acceptable, go/no-go documented.

State Tracking Schema

yaml
current_phase: "1|2|3|4"
phase_started: "ISO timestamp"
interviews_completed: "count by phase"
assumptions_tracked: "list with risk scores"
opportunities_identified: "list with scores"
decision_gates_evaluated: "G1|G2|G3|G4 status"
artifacts_created: "list of file paths"

Phase Transition Requirements

TransitionGateRequirements
1 to 2G15+ interviews, >60% confirmation, customer words, 3+ examples
2 to 3G2OST complete, top 2-3 identified, scores >8, team alignment
3 to 4G35+ users tested, >80% task completion, core flow usable, validated
4 to handoffG4Lean Canvas complete, 4 risks acceptable, go/no-go, stakeholder sign-off

Frequently asked questions

What does the Nw Discovery Workflow AI skill do?

4-phase discovery workflow with decision gates, phase transitions, success metrics, and state tracking

Why use Nw Discovery Workflow on TypingMind?

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

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

Which AI models can use Nw Discovery 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 Nw Discovery Workflow?

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

Is the Nw Discovery Workflow 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇