Product intelligence
Use when you need to model the product, its users, their workflows, risk, density, device, and environment before any interface decision is made.From its SKILL.md
npx -y skills add Suraj787/motif --skill product-intelligenceAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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SKILL.md
1.4 KB, 282 tokens by cl100k_base, as published. Nobody here has run it
Product Intelligence
Responsibility: Establish who the interface is for and what outcome is at stake, so every later decision is anchored in a real user need rather than aesthetics.
When to invoke
- Steps 4-5 of the root workflow, before design or interaction choices.
- Whenever a request lacks a stated user, task, or outcome.
Inputs
- The user request, repo signals, and any existing product docs or manifests.
Outputs
- A product model (purpose, product type: website vs web app, domain).
- A user model (audiences, jobs-to-be-done, expertise).
- A workflow model (tasks, frequency, criticality, data density).
- A risk model and an environment model (device, connectivity, context of use).
- A confidence level for each inference, marked as inference not fact.
Engine data + CLI
- Reads
product-intelligence/(product-model,user-model,workflows,risk-model,environment-model,confidence,manifests). ii classify,ii product model,ii product users,ii product workflows.
Notes
Never present a low-confidence inference as verified fact. State assumptions explicitly and flag what must be confirmed with the user or with evidence.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.