Original Reddit post

I work at Juicer Social (social feed embeds). We built these for ourselves, then made them installable for anyone:

• topic-scout: finds blog topics people are actually asking for. It pulls every Reddit and X thread mentioning your competitors through a social data API, filters out vendor noise, and clusters real questions into ranked topic ideas. Every quote comes with its source link.
• mention-scout: finds fresh threads where you can genuinely reply this week (“best tool for…?” asks, competitor complaints, unanswered mentions of your brand), with a suggested angle per reply. It refuses undisclosed promotion by design.
• juicer: a reference skill that teaches the agent our whole API, for building your own thing. The fun part: on the first real run, topic-scout flagged one account that had posted 29 near-identical “innocent question” posts across 20+ subreddits in a month, all name-dropping the same vendor. The astroturf detector is now a core feature, and the example report in the repo shows the catch. Under the hood there’s no runtime at all. Each skill is a single SKILL.md with the method written as instructions plus verbatim curl and jq commands (including the API gotchas we hit, like per-platform pagination cursors). First run interviews you about your brand and provisions a free API key with just your email. /plugin marketplace add juicer-io/skills /plugin install topic-scout@juicer-skills Repo: https://github.com/juicer-io/skills Would love feedback on the skill design itself. We went back and forth on shipping a Python engine vs pure instructions and landed on pure instructions for auditability. Curious what others building skills think about that tradeoff. submitted by /u/Ok-Consideration-117

Originally posted by u/Ok-Consideration-117 on r/ClaudeCode