North StarNS Academy
Stage 6/Claude as the Operating System/The Reddit OS
Lesson 6.4.1

Assembling the Full Operating System

4 min read 2 videos
How to Build a Reddit AI Agent That Finds Your Perfect Customers!
TaskAGI demo · unknown
6/10
Building Reddit Authority With AI Agents - From 0 to Industry Expert!
unknown · unknown
6/10

Copy-ready Claude prompt

Claude prompt
Run the full weekly scan: /reddit-weekly-scan, then apply reddit-intent-scorer to every result, then draft replies for anything scoring above {{intent_threshold}}, then run the humanizer pass. Stop before anything is marked ready-to-post, compile everything into a single weekly-digests/ entry for my review.

Learning objectives

  • Diagram the full daily/weekly Claude-run loop: research, subreddit discovery, thread analysis, opportunity detection, drafting, humanization, competitor monitoring, citation tracking, and reporting.
  • Place the human-in-the-loop gate at the correct point in that loop and explain why it cannot move.
  • Map each loop stage to a specific Skill, subagent, or MCP tool already built in this stage.
  • Evaluate a build-vs-buy tool decision using the GummySearch shutdown as the cautionary precedent.
  • Cite the Responsible Builder Policy requirements the loop's design must satisfy at every stage.

Prerequisites: Modules 6.1-6.3 in full.

Core concepts

Everything built across this stage now assembles into one repeatable pipeline, run on a schedule (a daily cron job, a GitHub Action, or a habitual manual morning run), each stage mapped to a concrete piece already in your reddit-ops repo. Subreddit discovery flags new relevant communities worth adding to your anchor list. Research subagents (Lesson 6.3.3) pull new and rising posts across your anchor subreddits via the Reddit MCP server (Lesson 6.3.2). Thread analysis runs reddit-intent-scorer (Lesson 6.2.1) against every new thread, scoring buying intent and flagging account credibility using the wrhilton-style pattern. Opportunity detection filters that output through Stage 4's own rules, under 10 comments, under an hour old gets priority. Drafting runs a reply-drafter or launch-post-drafter skill producing the 80/20, disclosed-mention draft. A humanization pass, the direct extension of Stage 3's work, strips AI-tell phrasing before a draft goes further. Competitor monitoring, its own subagent against the same subreddit set, tracks competitor mentions in parallel. Citation tracking checks whether past comments now surface inside Reddit Answers or Google's AI Overviews, tying back to Stage 2's GEO work. Reporting compiles everything into the weekly-digest format matching Stage 4/5's KPI dashboard.

The one component that never gets a Skill, subagent, or slash command is the last one: the human review gate. Every output from thread analysis onward lands in weekly-digests/ as a draft, and nothing crosses onto Reddit itself without a person reading it, editing it if needed, and posting it manually from their own disclosed account. This is not a temporary limitation awaiting a future automation upgrade, it is the permanent design, required by Reddit's March 2026 Responsible Builder Policy (declared purpose, scoped access, explicit consent before private communication, no reselling or training on Reddit data) and by every ethics lesson this course has taught since Stage 1. prawtools' own reddit_alert utility is a useful smaller-scale proof of the monitoring half working in isolation, a turnkey keyword-alert tool across subreddits, worth studying as a minimal version of what your full pipeline does at scale.

Treat the tooling layer beneath this as replaceable, not permanent, a lesson the market already taught the hard way. GummySearch, the long-standing default Reddit audience-research tool used by over 140,000 founders, shut down commercially on November 30, 2025, after failing to reach a commercial API agreement with Reddit (reppit.ai). Teams least disrupted were the ones who had built their own thin pipeline directly against Reddit's official Data API rather than depending on a third-party product's survival, exactly the pipeline this lesson assembled. Composio's hosted Reddit MCP toolkit for the Claude Agent SDK, enabling natural-language actions like "search trending posts about AI startups" without self-hosting a server, is a legitimate middle path if maintaining your own server becomes more overhead than it's worth, but the principle holds regardless of which layer you rent versus build: research and drafting can be as automated as you like; publishing cannot.

Video lessons

Supporting reading

Exercise

Draw your own version of the full loop diagram (see the Stage Project's reference diagram below for the structure), labeling each stage with the specific Skill, subagent, or MCP tool from Modules 6.2-6.3 that runs it.

Assignment

Write a one-page operating memo: your scheduled run cadence (daily or weekly), what triggers an entry into weekly-digests/, and an explicit statement of where the human gate sits and who holds it on your team.

Claude workflow

  • Skill idea: a "digest-compiler" skill that formats the outputs of every prior stage into one consistent, human-scannable weekly digest matching the Stage 4/5 KPI dashboard layout.
  • Automation: the entire research-through-drafting pipeline on a daily or weekly schedule, explicitly excluding the publish step, which remains permanently manual per this lesson's core argument.

Expected outcomes

  • Full loop diagram completed, every stage labeled with its actual implementing Skill/subagent/tool.
  • Written operating memo naming the run cadence and the specific human who holds the review gate.
  • Can explain the GummySearch precedent and why it argues for owning a thin, official-API-based pipeline.

Referenced resources

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