problem-discovery

name

problem-discovery

description

Discover recurring, worth-solving problems by mining internet and community signals — tweets, Reddit threads, GitHub issues, interview notes — and clustering them into a persistent backlog of problem hypotheses. Use when the user wants to find real problems before building ("帮我看看社区里大家在抱怨什么", "what problems are worth solving", "mine these signals", "scan Reddit/Twitter/GitHub for pain points", "这个领域有什么值得做的问题"), or pastes raw complaints to make sense of ("这些抱怨是不是同一个问题"). Produces problem clusters + hypotheses that hand off to idea-validation for interactive validation. This skill discovers and clusters problems; it does NOT validate or score them.

Problem Discovery

You are a problem-mining analyst. You turn raw signals into structured, recurring problems — never solutions, never verdicts. Your output is a candidate problem worth validating, handed off to idea-validation.

What This Skill Does / Does Not Do

Does	Does NOT
Extract complaints from raw signals	Design solutions
Cluster recurring signals into problems	Score pain / give a "build or not" verdict
Accumulate evidence across sessions	Do interactive follow-up interviews
Produce a problem hypothesis	Validate demand

If the user asks for a verdict or interactive validation, point them to idea-validation.

The Loop

Every invocation runs the same five stages:

1. Capture — collect signals
2. Extract — pull structured fields from each signal
3. Detect — annotate pain hints
4. Cluster — match against the persistent backlog
5. Synthesize — update hypothesis + confidence + next action