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Idea Validator

Community
aakashg
idea-validator

Use when the user asks to validate a product idea, stress-test an idea, evaluate whether an idea is good, or decide whether to build something. Do NOT use for prioritizing an existing backlog or reviewing a shipped feature — those need RICE scoring or a design review instead.

Overview

Publisheraakashg
Repositorypm-claude-skills
Skill nameidea-validator
Stars
116
Forks
35
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Idea Validator 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/aakashg/pm-claude-skills/tree/main/skills/idea-validator
  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/aakashg/pm-claude-skills.git /tmp/pm-claude-skills
mkdir -p .claude/skills
cp -r /tmp/pm-claude-skills/skills/idea-validator .claude/skills/idea-validator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Idea Validator 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 Idea Validator 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 Idea Validator 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.

Idea Validator

Stress-test a product idea across 5 dimensions and return a GO / ITERATE / STOP verdict with evidence.

Step 0 — Read first

SourcePathWhat to extract
Project contextCLAUDE.mdCompany, market, target users, current focus
Scoring rubricreferences/scoring-rubric.mdStrong/Moderate/Weak bar for each dimension
User's materialsany doc, deck, or notes they nameActual customer quotes, usage data, pricing research
Existing researchdocs/, research/ if presentPrior validation on the same problem

If the user names no materials, say so explicitly in the verdict. An idea validated only against your training data is a hypothesis, not a validation, and you must label it that way.

Constraints

Mandatory. These override the user's enthusiasm.

  • Every rating requires 3–5 sentences of specific reasoning. A rating with no evidence is invalid.
  • Never rate STRONG without a named comparable, a number, or a cited user behavior.
  • Never default to GO because the user is excited. Honesty is the deliverable.
  • Never treat "no competitors" as opportunity. It usually means no market. Say so.
  • Never recommend "build the MVP" as the first next step.
  • Flag every guess with ASSUMPTION: and name the data that would confirm or deny it.
  • Flag every missing input with [NEED: X].
  • Never give all five STRONGs unless the evidence is genuinely exceptional. Most ideas are a mix.
  • Name what is hard and why. "This could be challenging" is not a risk.

Existence check

Before scoring anything, verify three things:

  1. Problem — a specific pain, stated in the user's own words, with a frequency.
  2. User — a named segment: job title, company size, situation. "Everyone" and "businesses" fail this check.
  3. Evidence — one real signal: a customer quote, a support ticket volume, a competitor's pricing page, a workaround they observed.

If two of three are missing, refuse to score. Say which are missing and ask for exactly those. Scoring an idea with no user and no evidence produces a confident number built on nothing, which is worse than no analysis.

Step 1 — Understand the idea

Ask:

  1. What is the idea in one sentence?
  2. Who specifically has this problem? Job title, company size, situation.
  3. How are they solving it today?
  4. Why are you the right person or team to build this?

If the answer to #2 is vague, push back before proceeding. Every viable idea has a specific first customer.

Step 2 — Competitive scan

Run this before scoring Market Evidence. It grounds the rating in reality.

  • Direct competitors — name 2–3 with pricing, estimated size, and years in market.
  • Adjacent solutions — what are people cobbling together today? Spreadsheets + Slack + manual process is a strong signal.
  • Platform risk — which incumbent could ship this as a feature in one sprint?
  • Graveyard — has this been tried and failed? A failed predecessor is not disqualifying, but the user must explain what changed.

Output as a table:

| Competitor/Alternative | Type | Pricing | Est. Size | Key Weakness |
|------------------------|------|---------|-----------|--------------|
| [Name] | Direct | $X/mo | [size] | [gap] |
| [Name] | Adjacent | Free | [size] | [limitation] |
| DIY (spreadsheet) | Workaround | Free | Common | [pain point] |

If you lack real data here, write [NEED: competitive research on X] and cap Market Evidence at Moderate.

Step 3 — Score the five dimensions

Rate each Strong / Moderate / Weak. The full bar for each rating is in references/scoring-rubric.md — read it, do not score from intuition.

  1. Problem Severity — frequency, cost of status quo, evidence of workarounds
  2. Market Evidence — who is already paying, what, and is the market growing
  3. Solution Differentiation — the wedge, and whether it is defensible
  4. Feasibility — MVP in 4–6 weeks with a small team, and what the hard thing is
  5. Business Viability — monetization, willingness to pay, path to $1M ARR

Output template

Exact fields, exact order.

## Verdict: [GO / ITERATE / STOP]

[Two sentences. The decision and the single reason for it.]

## Scorecard

| Dimension                | Rating   | One-line reason |
|--------------------------|----------|-----------------|
| Problem Severity         | [rating] | [reason]        |
| Market Evidence          | [rating] | [reason]        |
| Solution Differentiation | [rating] | [reason]        |
| Feasibility              | [rating] | [reason]        |
| Business Viability       | [rating] | [reason]        |

## Competitive landscape
[table from Step 2]

## Reasoning
[3-5 sentences per dimension. Comparables, numbers, named assumptions.]

## Killer questions
[3 questions the founder must answer before building. Target the weakest dimensions.]

## Next 3 experiments
- **Experiment:** [what to do]
  **Cost:** [time and money]
  **Signal:** [what result raises or lowers confidence]
[x3, ordered by speed and cost]

## Assumptions and gaps
[Every ASSUMPTION: and [NEED: X] from above, listed together.]

Verdict thresholds: GO = strong across 4+ dimensions. ITERATE = promising, 1–2 dimensions need work, name the specific pivot. STOP = fundamental issues pivoting will not fix.

Example

Idea: AI meeting note-taker for sales teams.

Problem Severity: STRONG

Sales reps spend 30–45 minutes after every call writing CRM notes. At 5–8 calls per day that is 3+ hours of admin. Reps universally hate it — it is the #1 complaint in every sales team survey I have seen. The current workaround is telling: reps either skip notes entirely, which hurts the team, or write minimal notes, which loses deal context. Daily frequency, high cost, active workarounds.

Market Evidence: STRONG

Gong ($7B+ valuation), Chorus (acquired by ZoomInfo for $575M), and Fireflies.ai all prove willingness to pay at multiple price points. "Sales call recording" has strong and growing search volume. The shift to remote selling accelerated demand structurally, not cyclically.

Contrast — the same two ratings, done badly:

Problem Severity: STRONG — Taking meeting notes is annoying and people don't like doing it. This would save time. Market Evidence: STRONG — There are some competitors in this space which validates the idea.

The bad version gives ratings without evidence. No specifics, no data, no reasoning. It is worse than useless because it looks like analysis.

A full worked STOP verdict is in references/scoring-rubric.md.

Shortcuts Claude takes

What Claude might thinkWhy it's wrong
"The user is clearly excited, I'll soften the STOP"A softened STOP costs them six months. The verdict is the product.
"No competitors — that's white space"No competitors almost always means no market. Rate Market Evidence Weak and say why.
"I don't have market data, I'll estimate"An estimated TAM reads as real to the user. Write [NEED:] instead.
"Four Strongs and one Weak — round up to GO"The one Weak is usually the thing that kills it. Weak Business Viability alone is an ITERATE at best.
"Next step: build a prototype"The first step after validation is almost never building. Propose a demand test.
"The scorecard covers it, I'll skip the killer questions"The questions are where the founder finds the gap. Never drop the section.

Exit checklist

Not complete until every box is checked. Any [NEED: X] or [rating] placeholder left in the output is an automatic unchecked box — either fill it or state it explicitly in the Assumptions and gaps section.

  • Existence check passed, or the analysis was refused with reasons named
  • All 5 dimensions rated with 3–5 sentences of specific reasoning each
  • Every STRONG cites a named comparable, number, or observed behavior
  • Competitive table filled, or [NEED:] flagged and Market Evidence capped at Moderate
  • Verdict is one of GO / ITERATE / STOP, stated in the first line
  • If STOP, the reasoning explains why a pivot will not fix it
  • If ITERATE, the specific pivot is named
  • 3 killer questions target the weakest dimensions
  • 3 experiments listed with cost and signal
  • Every assumption is labeled ASSUMPTION: and collected at the end
  • No template placeholders remain

Next

  • If the verdict is GO or ITERATE → recommend /prd-writer to spec the first experiment, not the full product.
  • If Solution Differentiation was the weak dimension → recommend /competitive-analysis before any build work.
  • If the user wants to pitch this idea publicly → recommend /linkedin-post-writer, but only after the evidence exists.

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 Idea Validator AI skill do?

Use when the user asks to validate a product idea, stress-test an idea, evaluate whether an idea is good, or decide whether to build something. Do NOT use for prioritizing an existing backlog or reviewing a shipped feature — those need RICE scoring or a design review instead.

Why use Idea Validator on TypingMind?

Because you install it once and use it with any model. Idea Validator 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 Idea Validator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aakashg/pm-claude-skills/tree/main/skills/idea-validator. 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 Idea Validator?

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 Idea Validator?

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

Is the Idea Validator AI skill free?

Yes. It is published on GitHub by aakashg 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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