Add Reddit Search to Your Local Research Agent

Reddit is where real users complain, recommend, and debug in public. For research agents, Reddit threads contain signal that polished marketing pages do not: honest opinions, workarounds, and deal-breaker bugs. The problem is access. Reddit's API requires OAuth app registration, rate limits at 100 requests per minute per OAuth client, and returns raw post/comment data that needs parsing. For a local research agent, this is too much plumbing for a single data source.

Reddit API vs search API approach

• Reddit API: register app, get client ID and secret, handle OAuth token refresh, deal with rate limits, parse markdown body text
• Search API with a Reddit endpoint: one POST request, get Reddit posts ranked by relevance with title, URL, subreddit, score and comment count, no OAuth

The tradeoff is control vs convenience. The Reddit API gives you full thread data including all comments and votes. A search API gives you discovery -- which threads exist and are relevant -- but not the full comment tree.

Adding Reddit search to a local agent

import requests, os, json

API = "https://api.scavio.dev"
H = {"Authorization": f"Bearer {os.environ['SCAVIO_API_KEY']}"}

def search_reddit(query: str, limit: int = 10) -> list:
    """Search Reddit via Scavio. Returns top threads for a query."""
    resp = requests.post(
        f"{API}/api/v1/reddit/search",
        headers=H,
        json={"query": query},
        timeout=90,
    )
    results = resp.json()["data"].get("results", [])[:limit]
    return [
        {
            "title": r["title"],
            "url": r["url"],
            "snippet": (r.get("text") or "")[:300],
            "subreddit": r.get("subreddit"),
            "score": r.get("score"),
            "num_comments": r.get("num_comments"),
        }
        for r in results
    ]

Integrating into a research agent

A local research agent typically has a tool registry. Add the Reddit search as one tool alongside web search and document retrieval. The agent decides when to use Reddit based on the query type.

class ResearchAgent:
    def __init__(self):
        self.tools = {
            "web_search": self.web_search,
            "reddit_search": self.reddit_search,
        }

    def reddit_search(self, query: str) -> str:
        threads = search_reddit(query)
        return json.dumps(threads, indent=2)

    def web_search(self, query: str) -> str:
        resp = requests.post(
            f"{API}/api/v2/google",
            headers=H,
            json={"query": query},
            timeout=90,
        )
        results = [
            {"title": r.get("title"), "url": r.get("link"), "snippet": r.get("snippet", "")}
            for r in resp.json().get("organic_results", [])[:5]
        ]
        return json.dumps(results, indent=2)

    def research(self, topic: str) -> dict:
        """Run a research workflow: web search + Reddit for real opinions."""
        web_results = self.web_search(topic)
        reddit_results = self.reddit_search(topic)
        return {
            "web": json.loads(web_results),
            "reddit": json.loads(reddit_results),
        }

agent = ResearchAgent()
findings = agent.research("best database for real-time analytics 2026")
print(f"Web results: {len(findings['web'])}")
print(f"Reddit threads: {len(findings['reddit'])}")

What you get vs what you miss

The search approach gives you thread discovery: which subreddits discuss your topic, which threads are most relevant, and the opening text of each post. This is enough for many research tasks where you need sentiment and recommendations.

What you miss: full comment threads. A Reddit post with 200 comments might have the real answer buried in comment #47. The search endpoint returns the post title and body, not the full discussion. If deep comment analysis matters, make a follow-up call for that thread's comments.

Cost for a research-heavy workflow

A research agent that runs 10 Reddit searches and 10 web searches per research task uses 20 credits per task. At $0.01/credit, that is $0.10 per research task. 100 research tasks per month costs $10. The 50 free credits on signup cover two full research tasks at no cost.

Hybrid approach for deep threads

Use the search API for discovery, then pass the post_id of the threads that matter to Scavio's /api/v1/reddit/post/comments (1 credit per call) or to the Reddit API for full comments. This gives you the best of both: fast discovery without OAuth overhead, and deep data only when you need it. Most research tasks need discovery, not full thread dumps.