Agent Buzz

To curate noisy AI-agent tweets on X into concise narratives, this Skill monitors discourse over the last 24 hours, deduplicates candidates, scores signals, and outputs 2–4 narrative clusters with 6–9 tweets total.

Tweet deduplication for AI-agent discourse works by checking new candidates against the last 3 days of memory logs, skipping engagement-farming or promo threads to ensure only relevant chatter remains.

Yes, you need access to memory logs and engagement data to summarize AI-agent chatter, as the Skill requires these inputs for deduplication, signal scoring, and producing narrative-ready cluster insights.

The best way to extract actionable insights from AI-agent chatter on X is by clustering tweets into 2–4 narratives, scoring signals, and generating a compact report with cluster names, key insights, and source links.

Yes, you can get original source links when curating AI-agent tweets, as the Skill outputs a compact narrative report that includes cluster names, extracted insights, and direct links to the original tweets for reference.

Yes, a limitation when clustering X narratives is the output volume: the Skill strictly produces 2–4 narrative clusters containing a total of 6–9 tweets from the last 24 hours of AI-agent discourse.