Stop Wasting Hours on Manual Reddit Monitoring
If you've ever tried to track Reddit for mentions of your product, niche, or competitors, you know the pain. You open r/MachineLearning, r/learnpython, r/entrepreneur — scan hundreds of posts — and most of it is noise. An hour gone. Maybe you caught something useful, maybe not.
I automated this entire workflow with Python and the Claude API. It now runs on a schedule, scores every post for relevance and sentiment, and pings me only when something worth acting on shows up.
Here's the full setup.
Step 1: Install the Anthropic SDK
pip install anthropic praw requests
You'll need an Anthropic API key from console.anthropic.com. Set it as an environment variable:
export ANTHROPIC_API_KEY="sk-ant-..."
Step 2: Fetch Reddit Posts
You can use PRAW (the official Reddit API wrapper) or plain requests against the JSON endpoint. Here's the lightweight requests approach — no OAuth needed for read-only:
import requests
def fetch_reddit_posts(subreddit: str, limit: int = 25) -> list[dict]:
url = f"https://www.reddit.com/r/{subreddit}/new.json"
headers = {"User-Agent": "RedditMonitor/1.0"}
params = {"limit": limit}
resp = requests.get(url, headers=headers, params=params, timeout=10)
resp.raise_for_status()
posts = []
for item in resp.json()["data"]["children"]:
d = item["data"]
posts.append({
"id": d["id"],
"title": d["title"],
"selftext": d.get("selftext", "")[:500],
"score": d["score"],
"url": f"https://reddit.com{d['permalink']}",
"created_utc": d["created_utc"],
})
return posts
Call this for each subreddit you want to monitor:
subreddits = ["MachineLearning", "learnpython", "entrepreneur", "SideProject"]
all_posts = []
for sub in subreddits:
all_posts.extend(fetch_reddit_posts(sub, limit=20))
Step 3: Score Posts with Claude API
Now we pass the posts to Claude for sentiment and relevance scoring. I batch them to keep API costs low — one call handles up to 15 posts at a time.
import anthropic
import json
client = anthropic.Anthropic()
def score_posts(posts: list[dict], topic: str) -> list[dict]:
if not posts:
return []
payload = [
{"id": p["id"], "title": p["title"], "body": p["selftext"]}
for p in posts
]
prompt = f"""You are a Reddit monitoring assistant. The user tracks the topic: "{topic}".
For each post below, return a JSON array with:
- id: the post id
- relevance: 0-10 (how relevant to the topic)
- sentiment: "positive", "neutral", or "negative"
- reason: one sentence why
Posts:
{json.dumps(payload, indent=2)}
Return ONLY valid JSON. No explanation outside the array."""
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}]
)
raw = message.content[0].text.strip()
if raw.startswith("```
"):
raw = raw.split("
```")[1]
if raw.startswith("json"):
raw = raw[4:]
scores = json.loads(raw.strip())
score_map = {s["id"]: s for s in scores}
for post in posts:
post.update(score_map.get(post["id"], {}))
return posts
Step 4: Filter High-Signal Posts and Alert
Set a threshold — anything with relevance >= 7 gets surfaced. You can print it, log it, or fire a webhook.
def monitor_reddit(topic: str, subreddits: list[str], threshold: int = 7):
all_posts = []
for sub in subreddits:
all_posts.extend(fetch_reddit_posts(sub, limit=20))
scored = score_posts(all_posts, topic)
high_signal = [
p for p in scored
if p.get("relevance", 0) >= threshold
]
if not high_signal:
print("No high-signal posts found.")
return
print(f"\n=== {len(high_signal)} High-Signal Posts ===\n")
for post in sorted(high_signal, key=lambda x: x.get("relevance", 0), reverse=True):
print(f"[{post['relevance']}/10] {post['title']}")
print(f" Sentiment: {post['sentiment']}")
print(f" Reason: {post['reason']}")
print(f" URL: {post['url']}\n")
monitor_reddit(
topic="AI automation tools for developers",
subreddits=["MachineLearning", "learnpython", "entrepreneur", "SideProject"]
)
Example output:
=== 3 High-Signal Posts ===
[9/10] I built an AI agent that monitors Slack + Reddit for competitor mentions
Sentiment: positive
Reason: Directly describes the automation topic with code included
URL: https://reddit.com/r/SideProject/...
[8/10] Looking for tools to automate social media monitoring
Sentiment: neutral
Reason: User actively seeking solutions in this space
URL: https://reddit.com/r/entrepreneur/...
What This Replaces
- 2-3 hours of manual Reddit scrolling per day
- Missed mentions because you can't be everywhere
- Gut-feel relevance scoring that's inconsistent
The Claude API does the reasoning — you just act on what it surfaces.
Extend It
A few directions I've taken this further:
- Schedule it: Run with cron or GitHub Actions every hour
- Deduplicate: Store post IDs in SQLite so you don't re-score old posts
- Webhook alerts: Fire to Slack, Discord, or Telegram when relevance >= 9
- Track competitors: Add competitor names to the topic string — Claude picks them out naturally
Want the full browser automation starter kit? I packaged everything here: https://knightops.gumroad.com/l/ytakiy — includes pre-built Claude API agent templates.
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