Works with the AI tools you already use
Digital Product Verdict
by Alerya
A rigorous validation engine that stress-tests digital product ideas using evidence-based commercial scoring.
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See it in action
You say
Use Brutal Mode to validate this idea: a printable weekly planner for busy women. I have not conducted customer research or tested willingness to pay.
Your agent does
Concept Score: 47/100 — WEAK
Evidence Confidence: LOW
Strongest Evidence: The concept addresses a recognizable recurring need: weekly organization.
Evidence Gap: No evidence from a specific target customer demonstrates willingness to choose or pay for this product.
Substitution Risk: HIGH
Differentiation: GENERIC
VERDICT: MODIFY
The underlying need is credible, but “busy women” is too broad and the product has no compelling advantage over free printables, notebooks, calendar apps, Canva templates, or AI-generated planners.
NEXT DECISION: NARROW AUDIENCE
Identify a specific buyer and planning problem before building the full product.
What you get
About this skill
The problem
Digital product creators often invest significant time in ideas based mainly on intuition, only to discover weak buyer interest after launch. Many AI tools encourage promising-sounding concepts without adequately challenging buyer motivation, differentiation, substitution risk, or the available evidence.
What it does
- Evaluates digital product concepts using a 100-point Commercial Structure Score.
- Separates Concept Strength from Evidence Confidence to prevent false certainty.
- identifies competing substitutes such as free resources, AI tools, spreadsheets, templates, and manual workflows.
- Detects friction that could cause customers to purchase a product but never use it.
- Produces a clear BUILD, VALIDATE, MODIFY, PIVOT, or DROP verdict.
- Recommends the strongest version of the idea and the smallest useful MVP.
- Includes an optional Brutal Mode for aggressively stress-testing weak assumptions.
Why this beats prompting it yourself
One-off prompts often produce inconsistent scoring, vague recommendations, and excessive encouragement. This skill applies a repeatable 14-stage validation process and a strict evidence hierarchy.
It distinguishes assumptions, stated interest, observed behavior, and actual payment evidence. A concept can therefore receive a strong score while still being correctly labeled as having LOW Evidence Confidence.
Use cases
- Stress-test a Notion template, ebook, printable, spreadsheet, or AI workflow before building it.
- Decide whether an underperforming product should be modified, repositioned, or abandoned.
- Identify the smallest MVP needed to test the central product hypothesis.
- Compare an idea with free tools, manual workflows, and competing products.
- Find meaningful differentiation beyond aesthetics, extra pages, or generic bonuses.
- Turn customer interviews, prototype feedback, preorders, sales, and usage data into a more evidence-based decision.
Known limitations
- The skill requires an initial product idea and works best when the user supplies information about the intended buyer.
- It does not independently access private marketplace sales figures or internal data from platforms such as Etsy or Gumroad.
- Live external research depends on the tools available to the AI agent using the skill.
- Its conclusions are only as reliable as the evidence provided and cannot guarantee commercial success.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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