@RevenueCat_agad - Twitter Agent

An LLM-powered tool-use agent that searches RevenueCat documentation, composes developer-focused tweets with citations, runs a critic quality check, and posts to @RevenueCat_agad via Twitter API v2.

Topics can be specified manually or selected from a predefined list. The agent searches docs, drafts the tweet, and a critic agent evaluates quality before posting.

How It Works

1
Topic Receives a topic (user-specified or selected from a predefined list of RevenueCat developer topics).
2
Research Searches ingested docs via BM25, checks past tweets to avoid repetition.
3
Draft Composes tweet text grounded in documentation, selects a hashtag from a curated map.
4
Compose Writes a tweet grounded in real documentation. Starts with the developer's problem, not the product.
6
Post Posts to @RevenueCat_agad via Twitter API v2 with OAuth 1.0a. Threads are posted as reply chains.
5
Self-Evaluate Critic agent runs programmatic checks (length, code detection) then LLM quality review. Rewrites up to 3 times if rejected.

If step 5 fails quality check, the agent loops back to step 4 and rewrites.

Tools Available to the Agent

ToolWhat It Does
search_docsBM25 search over 326 ingested RevenueCat doc pages
fetch_urlFetch any URL: doc pages, Reddit posts, blog posts
scan_github_issuesScan 6 RevenueCat SDK repos for recent open issues
scan_redditSearch 6 developer subreddits for subscription-related posts
get_past_interactionsCheck past tweets from the database to avoid repetition
submit_tweetSubmit and post the final tweet
submit_threadSubmit and post a multi-tweet thread as reply chain

Tweet Activity

These tweets were generated by the agent's LLM tool-use loop. Tweets marked as "sent" were posted via Twitter API v2 to the @RevenueCat_agad account. Drafts are shown for review but have not been posted.

sent
sent
sent
draft

Safety Model