Product Discovery

Explore opportunities and assumptions, plan experiments and organize findings.

Available in app
A notebook, hypothesis cards and magnified evidence token suggest product experiments.

Overview

Before committing to building, break the product idea into small verifiable bets. Pin one measurable outcome (baseline and target horizon), then grow an opportunity-solution tree: under the outcome, opportunities backed by user evidence; under those, candidate solutions; under those, the fastest-learning experiments — at least three distinct opportunities before converging.

Then put assumptions on the table: do users want it, does the business hold, can it be built, is it usable — each scored by risk and uncertainty, tested from the riskiest outward. On the problem side, interviews confirm frequency, pain and willingness to act, and weak signals die early; on the solution side, prototypes test concept and value by watching behavior, not stated preference.

The cadence is a one-to-two-week discovery loop with explicit hypotheses, daily evidence reviews and a closing call: proceed, pivot or stop. What stays in your workspace is the tree, the assumption map and the loop plan — not another report nobody rereads.

Where it helps

  • Build an Opportunity Solution Tree for a feature direction and mark evidence gaps
  • Turn 'I feel we should build this' into a risk-scored assumption map
  • Design an interview guide that tests frequency, severity and willingness
  • Plan a two-week discovery sprint with proceed/pivot/stop criteria
#discovery#hypothesis#validation#evidence

Examples

Examples describe the request and the shape of the expected deliverable; they are not completed run results.

Example prompt

Direction 'handwriting annotation for iPad users': give the outcome metric and an opportunity-tree skeleton, attach every opportunity to one of the three interview quotes I supplied, and mark gaps plainly.

Expected output

A tree with an evidence map: every opportunity points back to your interview material, unsupported spots flagged, not back-filled.

Example prompt

Assumption-map that tree: list all four assumption classes, score by risk and uncertainty, and give the three riskiest each a small experiment finishable within two weeks.

Expected output

A scored assumption table plus three experiments — hypothesis, measure, sample, pass bar — with a two-week plan.

Requirements and limits

Install platforms
iOS: iOS · Android: Android
Script runtime
No script runtime (guidance and workflow)
Minimum app version
iOS: 1.7.59
Reviewed permission scope

iOS · Android

Capabilities
Read workspace filesWrite workspace files
Review decision
Approved
Review stage
Static content review
Reviewed on
2026-10-28
Implementation and runtime details
Adaptation stage
frozen

iOS

Capabilities
Read workspace filesWrite workspace files

Android

Capabilities
Read workspace filesWrite workspace files

License and source

Source and trace details

License

MIT

MIT (root LICENSE)

The pinned skill subtree and shipped references were audited; full applicable license and per-file adaptation/asset notes are preserved under references/licenses/ and references/PROVENANCE.md.

Image and material attribution

Image attribution
Floe original, AI-assisted illustration.
Source
https://github.com/alirezarezvani/claude-skills
Upstream path
product-team/skills/product-discovery
Upstream pin
6d2f02ea07
Source checked
2026-10-26
Publisher
JiangNanGenius
Publication commit (retrieval)
25e07dbeeb6cc93c2fe83ddc72a34302cc40832a
Audited source commit
84c524b6fb483e4cad94db076e7d9c9962966c19
Signed catalog digest
iOS 46196ba57ed7ea7f22085e74b113207f31193e820ab8983cf7a60eee953f2340 · Android 16de89d019e2057804a40f215485ccb09d5495a25864b34d681168eeaf8f9697
Publication snapshot (UTC)
2026-10-31

Publication commit 25e07dbeeb, audited source 84c524b6fb; catalog digest iOS 46196ba57ed7… · Android 16de89d019e2….

Versions and status

Version records ship with the signed catalog; the target and released versions are shown below.

Adaptation
Ready
Publication state
Curated skills are available
Released version
1.0.1