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Auto-Commenter is a Claude-oriented automation project built to help users write and post comments that sound natural and context-aware in targeted online communities. It centers on learning a user’s writing style from their real comment history, then applying that style to generate responses that feel consistent with the user rather than generic template text. The workflow emphasizes deeper post analysis so the system can respond to what is actually being discussed, instead of replying with shallow engagement bait. It is framed as a “skill” that can be configured to operate in specific communities, aiming to reduce the repetitive work of staying active while still keeping comments personalized. Because it is designed for ongoing use, it typically includes setup steps for credentials, configuration, and guardrails that define where and how it should comment.
Features
- Writing-style learning from a user’s existing comment history
- Context-aware post analysis before drafting a response
- Personalized comment generation aligned to target communities
- Configurable community targeting and behavior settings
- Repeatable workflow intended for ongoing engagement routines
- Designed to minimize “generic AI voice” through style constraints
Project Samples
