How to Research Reddit Discussions with an AI Agent

Reddit is where people explain their reasoning: why they chose a tool, what made them leave, what they wish existed. That makes it the best qualitative research surface on the social web, and also a slow one to read by hand. An AI agent with a Reddit research skill compresses the loop: one question in, and back comes a structured report of where the discussion lives, what the community praises and complains about, and the quotable posts behind each finding.

This tutorial uses reddit-research, an open-source skill from our collection at Xpoz. It searches the Xpoz index of Reddit posts and comments (part of a four-platform index covering billions of posts, free tier available), which is also why no Reddit API key appears anywhere in the setup.

What the Report Contains

A research run answers "what does Reddit think about X?" in five structured sections:

• Subreddit distribution: where the discussion actually happens, with post counts and average scores per community. The same product gets different treatment in r/programming and r/productivity, and knowing which conversation dominates is itself a finding.
• What people love: recurring praise themes with supporting quotes.
• Pain points and complaints: the frustrations and feature requests, which for product teams is usually the section that pays for the run.
• Comparisons and alternatives: how the community weighs the product against rivals, and which alternatives keep coming up.
• Notable quotes and top threads: the highest-engagement posts, quoted with attribution and score, ready to drop into a research doc.

Reading Reddit's Native Signals

Reddit ships with sentiment signals no other platform has, and the skill uses them instead of ignoring them. Score is community agreement: a 1,200-upvote complaint is a communal verdict, not one person's bad day. The score-to-comments ratio classifies threads: high score with few comments means consensus; low score with a long comment chain means live controversy worth reading closely.

The other structural fact: comments often hold what posts don't. Asks, workarounds, and dissents live in comment chains under nominally unrelated posts, so the skill searches comments as well as posts and can pull a full thread with its comment tree when a candidate deserves a close read. Prioritizing high-score, high-comment threads first is how a 300-post result set gets read in minutes instead of days.

Worked Queries

Query construction does the aiming. Three patterns cover most research intents:

Product feedback:
"Cursor" OR "Cursor IDE" — then let themes emerge

Comparison mining:
"Cursor vs" OR "Cursor alternative" OR "switched from Cursor"

Feedback with intent:
"Cursor" AND ("love" OR "hate" OR "switched" OR "review")

Scope to a community when the question is community-specific ("what is r/machinelearning saying about open-source models?"), and widen the window when a niche topic runs thin. Sparse results on a 7-day window are a coverage note, not a verdict of silence; the skill widens or rephrases before concluding either way.

Setup and First Run

Install the skill (Claude Code shown; the same folder works in any SKILL.md-compatible agent):

git clone https://github.com/XPOZpublic/xpoz-agent-skills.git
cp -r xpoz-agent-skills/skills/reddit-research ~/.claude/skills/

Connect data access via the remote MCP server (OAuth, no keys) or a free SDK key from xpoz.ai/get-token (up to 75,000 results free):

claude mcp add --transport http --scope user xpoz https://mcp.xpoz.ai/mcp

Then ask:

"What does Reddit think about Cursor IDE?"

"Search Reddit for people complaining about Zapier pricing"

"What tools are indie hackers using for automation? Check Reddit"

"What's r/machinelearning saying about open-source LLMs?"

For datasets rather than reports ("give me every post mentioning our brand this quarter"), the same search exports to CSV for spreadsheet or pandas work. And for standing coverage of your own brand or category subreddits, tracked keywords and tracked subreddits collect continuously in the background, which deepens every future run.

FAQ

Can I research Reddit without a Reddit API key?

Yes. An indexed data layer maintains its own searchable copy of Reddit posts and comments, so the agent queries the index instead of Reddit's official API. One sign-in to the data layer replaces Reddit developer credentials entirely.

How far back does Reddit search go?

The Xpoz index provides a rolling 60-day window, with tracked items accumulating deeper coverage over time. Multi-year history is a different problem with its own options; see the historical-data guide linked below.

What do Reddit scores actually tell you?

Score is built-in community sentiment. High score with few comments signals consensus; low score with many comments signals controversy. The patterns sort settled opinion from live debate before you read a single thread.

Can I focus the research on one subreddit?

Yes: scope the request to the community, or track the subreddit for continuous collection. The report keeps communities separate because context changes what the same words mean.

Next Steps

• Monitoring your own brand on Reddit specifically is covered in How to Monitor Reddit Brand Mentions.
• Choosing a Reddit data source, official API included, is mapped in Best Reddit API Alternatives in 2026.
• For multi-year archives after Pushshift's restriction, see How to Get Historical Reddit Data After Pushshift.
• The full skills collection and install pattern: How to Add Social Media Skills to Your AI Agent.