dsh-idea

The hardest part of building a product is rarely the code; it is confirming that the problem is worth solving. dsh-idea pulls in the scattered external signals that most teams overlook or misread: community threads, issue trackers, user reviews, competitor pages and trend reports. It turns them into a repeatable validation loop - scan bounded public pages, extract pain-point signals, cluster them into opportunity themes by user and context, draft multiple solution directions, and generate a minimum falsifiable experiment complete with audience, steps, thresholds and a decision rule. A hot topic does not become a demand proof, and a single complaint does not become a product requirement. Instead, evidence-strength scoring and structured interview guides (JTBD, Mom Test, switching cost, critical event) turn a hunch into a testable hypothesis.

The workflow spans the full path from signal collection to opportunity handoff: bounded public URL snapshots, normalization of Markdown, CSV, TSV, JSON and JSONL research records, multi-dimensional filtering by keyword, user, scene, source, date and evidence strength, signal ranking, theme clustering, candidate direction drafting, experiment planning, and finally an idea_review artifact paired with an Opportunity Solution Tree. Every artifact carries a version, stable ID, content fingerprint and freshness window, so downstream plugins - dsh-product for product definition, dsh-business for commercial review - receive a traceable, auditable record. A partial handoff is explicitly flagged as a research gap, never silently treated as a requirement.

It is built for indie developers, product managers and early-stage teams who want to ground product decisions in external evidence rather than intuition, and for anyone operating within the six-plugin collaboration system who needs a structured, contract-defined entry point for demand discovery.