search narrative candidate topics by keyword

Reverse-searches topic candidates from a human keyword to map a fuzzy narrative into the platform's topic taxonomy. Input is keyword (e.g., "RWA", "AI Agent", "Restaking"). Output is a list of candidate topics with topic_id, match rationale/keyword overlap, and a trend/heat summary. Recommended: let the client-side LLM cluster/name/summarize the candidates.