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Nw Pdr Review Criteria

Organization
nWave-ai
nw-pdr-review-criteria

Evidence quality validation and decision gate criteria for product discovery reviews

Overview

PublishernWave-ai
RepositorynWave
Skill namenw-pdr-review-criteria
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 Pdr Review Criteria 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-pdr-review-criteria
  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-pdr-review-criteria .claude/skills/nw-pdr-review-criteria
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Pdr Review Criteria 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 Pdr Review Criteria 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 Pdr Review Criteria 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.

Review Criteria -- Product Discovery Review

Evidence Quality Validation

Past Behavior Indicators (Good)

"Tell me about the last time..." | "When did you last..." | "What happened when..." | "Walk me through how you..." | "What did you try..." | "How much have you spent on..." Specific dates, dollar amounts, named tools, concrete examples, emotional frustration language

Future Intent Red Flags (Reject)

"Would you use/pay/like..." | "Do you think..." | "Imagine if..." | "What if we..." Flag and reject if >20% of evidence is future-intent.

Validation Thresholds

  • Past behavior ratio: >80% (reject if fail, require re-interview)
  • Specific examples: min 3 concrete per finding (warn if fail)
  • Customer language: quotes in customer words, not paraphrased (warn if fail)

Sample Size Minimums

PhaseMinimumHigh ConfidenceNotes
1: Problem510Interviews required
2: Opportunity1020Quantitative supplements, not replaces
3: Solution5 per iteration3 iterations maxBefore decision
4: Viability5--Stakeholder review required

Pivot decision rule: min 5 consistent signals. Block decisions on fewer.

Decision Gate Criteria

G1: Problem to Opportunity

Proceed: 5+ confirm pain + willingness to pay | Pivot: differs from expected | Kill: <20% confirm Checks: 5+ interviews, >60% confirmation, customer words, 3+ examples

G2: Opportunity to Solution

Proceed: top 2-3 score >8 (0-20) | Pivot: new opportunities | Kill: all low-value Checks: OST complete with 5+, scores correct (Importance + Max(0, Importance - Satisfaction)), top >8/20

G3: Solution to Viability

Proceed: >80% task completion, usability validated | Pivot: needs refinement | Kill: fundamental blocks Checks: 5+ users/iteration, >80% completion, core flow usable, value validated

G4: Viability to Build

Proceed: 4 risks addressed, model validated | Pivot: adjustment needed | Kill: no viable model Checks: Lean Canvas complete, all risks green/yellow, stakeholder sign-off

Bias Types

Confirmation Bias (critical)

Signals: only positive quotes | skeptics not interviewed | disconfirming evidence dismissed | same questions for "right" answers Fix: include skeptics, actively seek disconfirming evidence

Selection Bias (high)

Signals: all existing customers | no churned/non-adopters | lacks diversity | single-enthusiast referral chain Fix: random/diverse selection, include skeptics and non-users

Discovery Theater (critical)

Signals: conclusion decided before research | findings match hypothesis perfectly | no surprises | idea-in = idea-shipped Fix: track idea evolution, expect 50%+ ideas to change

Sample Size Problem (high)

Signals: major decisions on 2-3 interviews | single quote as "validation" | pivot on one signal Fix: min 5 interviews per segment, 5+ signals for decisions

Anti-Patterns

Interview Anti-Patterns

PatternDetectionBadGoodSeverity
Leading questionsSuggests desired answer"Don't you think this would save time?""Tell me about the last time you tried to save time on this"high
Future-intentHypothetical behavior"Would you use this feature?""What have you tried to solve this problem?"critical
Compliments as validationAccepting "that's cool""They loved the idea!""They committed to follow-up and referral"high
Talking > listening>30% interviewer talkLong questions, short responsesOpen questions, extended answersmedium

Process Anti-Patterns

PatternDetectionSeverity
Skipping to solutionsSolution before problem validatedcritical
Demographic segmentationSegments by demographics not jobsmedium
Building before testingCode before Phase 3critical

Strategic Anti-Patterns

PatternDetectionSeverity
Premature pivotingDirection change on 1-2 signals (need 5+)high
Solution loveDefending despite evidence, dismissing criticshigh
Sole source of truthOnly quant OR qual, not bothmedium

Pre-Approval Checklist

Evidence Quality

  • Past behavior ratio >80% | [ ] No critical future-intent | [ ] Customer language preserved

Sample Sizes

  • Phase 1: 5+ | [ ] Phase 2: 10+ | [ ] Phase 3: 5+/iteration | [ ] Phase 4: 5+ with stakeholders

Decision Gates

  • All gates properly evaluated | [ ] Criteria documented with evidence | [ ] Decision justified

Bias Check

  • No confirmation bias | [ ] No selection bias | [ ] No discovery theater | [ ] Sample size adequate

Anti-Patterns

  • No critical interview anti-patterns | [ ] No critical process anti-patterns | [ ] No critical strategic anti-patterns

Approval Decision

  • Approved: all checks pass, no critical issues. Formal handoff to product-owner.
  • Conditionally approved: minor issues only (no critical/high). Approval with recommendations.
  • Rejected: any critical/high issue. Structured rejection with remediation. Blocks handoff.

Frequently asked questions

What does the Nw Pdr Review Criteria AI skill do?

Evidence quality validation and decision gate criteria for product discovery reviews

Why use Nw Pdr Review Criteria on TypingMind?

Because you install it once and use it with any model. Nw Pdr Review Criteria 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 Pdr Review Criteria in TypingMind?

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

Which AI models can use Nw Pdr Review Criteria?

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 Pdr Review Criteria?

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

Is the Nw Pdr Review Criteria 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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