tweet-engage

To generate tweets from on-chain signals, this skill reads current on-chain state and engagement history from memory files like x-performance.jsonl, then outputs 1-2 ready-to-publish drafts aligned with your strategy.

Drafting tweets based on engagement history requires reading memory/MEMORY.md, memory/x-performance.jsonl, memory/x-strategy.md, memory/x-accounts.json, and the last 3 days of memory/logs to determine relevant themes.

Maintaining voice consistency during content generation is achieved by referencing recent logs and memory/x-strategy.md, ensuring the 1-2 tweet drafts conform to established voice rules and current strategy constraints.

Yes, you can create tweet drafts without manual writing because the skill automatically transforms on-chain state and engagement data into 1-2 ready-to-publish tweets conforming to length constraints.

The best way to turn on-chain memory logs into ready-to-publish content is using a skill that parses the last 3 days of logs and x-strategy.md to surface themes, outputting tweet drafts that conform to voice rules.