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Reddit Api

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alinaqi
reddit-api

Reddit API with PRAW (Python) and Snoowrap (Node.js)

Overview

Publisheralinaqi
Repositorymaggy
Skill namereddit-api
Stars
707
Forks
57
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by alinaqi on GitHub. Read the source before you install it.

Installation

Install the Reddit Api AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/alinaqi/maggy/tree/main/skills/reddit-api
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/alinaqi/maggy.git /tmp/maggy
mkdir -p .claude/skills
cp -r /tmp/maggy/skills/reddit-api .claude/skills/reddit-api
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reddit Api in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Reddit Api on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Reddit Api is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Reddit API Skill

For integrating Reddit data into applications - fetching posts, comments, subreddits, and user data.

Sources: Reddit API Docs | OAuth2 Wiki | PRAW Docs


Setup

1. Create Reddit App

  1. Go to https://www.reddit.com/prefs/apps
  2. Click "Create App" or "Create Another App"
  3. Fill in:
    • Name: Your app name
    • App type:
      • script - For personal use / bots you control
      • web app - For server-side apps with user auth
      • installed app - For mobile/desktop apps
    • Redirect URI: http://localhost:8000/callback (for dev)
  4. Note your client_id (under app name) and client_secret

2. Environment Variables

bash
# .env
REDDIT_CLIENT_ID=your_client_id
REDDIT_CLIENT_SECRET=your_client_secret
REDDIT_USER_AGENT=YourApp/1.0 by YourUsername
REDDIT_USERNAME=your_username        # For script apps only
REDDIT_PASSWORD=your_password        # For script apps only

User-Agent Format: <platform>:<app_id>:<version> (by /u/<username>)


Rate Limits

TierLimitNotes
OAuth authenticated100 QPMPer OAuth client ID
Non-authenticatedBlockedMust use OAuth
  • Limits averaged over 10-minute window
  • Include User-Agent header to avoid blocks
  • Respect X-Ratelimit-* response headers

Python: PRAW (Recommended)

Installation

bash
pip install praw
# or
uv add praw

Script App (Personal Use / Bots)

python
import praw
from pydantic_settings import BaseSettings

class RedditSettings(BaseSettings):
    reddit_client_id: str
    reddit_client_secret: str
    reddit_user_agent: str
    reddit_username: str
    reddit_password: str

    class Config:
        env_file = ".env"

settings = RedditSettings()

reddit = praw.Reddit(
    client_id=settings.reddit_client_id,
    client_secret=settings.reddit_client_secret,
    user_agent=settings.reddit_user_agent,
    username=settings.reddit_username,
    password=settings.reddit_password,
)

# Verify authentication
print(f"Logged in as: {reddit.user.me()}")

Read-Only (No User Auth)

python
import praw

reddit = praw.Reddit(
    client_id="your_client_id",
    client_secret="your_client_secret",
    user_agent="YourApp/1.0 by YourUsername",
)

# Read-only mode - can browse, can't post/vote
reddit.read_only = True

Common Operations

python
# Get subreddit posts
subreddit = reddit.subreddit("python")

# Hot posts
for post in subreddit.hot(limit=10):
    print(f"{post.title} - {post.score} upvotes")

# New posts
for post in subreddit.new(limit=10):
    print(post.title)

# Search posts
for post in subreddit.search("pydantic", limit=5):
    print(post.title)

# Get specific post
submission = reddit.submission(id="abc123")
print(submission.title)
print(submission.selftext)

# Get comments
submission.comments.replace_more(limit=0)  # Flatten comment tree
for comment in submission.comments.list():
    print(f"{comment.author}: {comment.body[:100]}")

Posting & Voting (Requires Auth)

python
# Submit text post
subreddit = reddit.subreddit("test")
submission = subreddit.submit(
    title="Test Post",
    selftext="This is the body of my post."
)

# Submit link post
submission = subreddit.submit(
    title="Check this out",
    url="https://example.com"
)

# Vote
submission.upvote()
submission.downvote()
submission.clear_vote()

# Comment
submission.reply("Great post!")

# Reply to comment
comment = reddit.comment(id="xyz789")
comment.reply("I agree!")

Streaming (Real-time)

python
# Stream new posts
for post in reddit.subreddit("python").stream.submissions():
    print(f"New post: {post.title}")
    # Process post...

# Stream new comments
for comment in reddit.subreddit("python").stream.comments():
    print(f"New comment by {comment.author}: {comment.body[:50]}")

User Data

python
# Get user info
user = reddit.redditor("spez")
print(f"Karma: {user.link_karma + user.comment_karma}")

# User's posts
for post in user.submissions.new(limit=5):
    print(post.title)

# User's comments
for comment in user.comments.new(limit=5):
    print(comment.body[:100])

TypeScript / Node.js: Snoowrap

Installation

bash
npm install snoowrap
# or
pnpm add snoowrap

Setup

typescript
import Snoowrap from "snoowrap";

const reddit = new Snoowrap({
  userAgent: "YourApp/1.0 by YourUsername",
  clientId: process.env.REDDIT_CLIENT_ID!,
  clientSecret: process.env.REDDIT_CLIENT_SECRET!,
  username: process.env.REDDIT_USERNAME!,
  password: process.env.REDDIT_PASSWORD!,
});

// Configure rate limiting
reddit.config({
  requestDelay: 1000,  // 1 second between requests
  continueAfterRatelimitError: true,
});

Common Operations

typescript
// Get hot posts from subreddit
const posts = await reddit.getSubreddit("typescript").getHot({ limit: 10 });
posts.forEach((post) => {
  console.log(`${post.title} - ${post.score} upvotes`);
});

// Search posts
const results = await reddit.getSubreddit("programming").search({
  query: "typescript",
  sort: "relevance",
  time: "month",
  limit: 10,
});

// Get specific post
const submission = await reddit.getSubmission("abc123").fetch();
console.log(submission.title);

// Get comments
const comments = await submission.comments.fetchAll();
comments.forEach((comment) => {
  console.log(`${comment.author.name}: ${comment.body.slice(0, 100)}`);
});

Posting

typescript
// Submit text post
const post = await reddit.getSubreddit("test").submitSelfpost({
  title: "Test Post",
  text: "This is the body.",
});

// Submit link
const linkPost = await reddit.getSubreddit("test").submitLink({
  title: "Check this out",
  url: "https://example.com",
});

// Vote and comment
await post.upvote();
await post.reply("Great post!");

Direct API (No Library)

Python with httpx

python
import httpx
import base64
from pydantic import BaseModel

class RedditClient:
    def __init__(self, client_id: str, client_secret: str, user_agent: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.user_agent = user_agent
        self.access_token: str | None = None
        self.client = httpx.AsyncClient()

    async def authenticate(self) -> None:
        """Get application-only OAuth token."""
        auth = base64.b64encode(
            f"{self.client_id}:{self.client_secret}".encode()
        ).decode()

        response = await self.client.post(
            "https://www.reddit.com/api/v1/access_token",
            headers={
                "Authorization": f"Basic {auth}",
                "User-Agent": self.user_agent,
            },
            data={
                "grant_type": "client_credentials",
            },
        )
        response.raise_for_status()
        self.access_token = response.json()["access_token"]

    async def get_posts(self, subreddit: str, sort: str = "hot", limit: int = 10) -> list[dict]:
        """Get posts from a subreddit."""
        if not self.access_token:
            await self.authenticate()

        response = await self.client.get(
            f"https://oauth.reddit.com/r/{subreddit}/{sort}",
            headers={
                "Authorization": f"Bearer {self.access_token}",
                "User-Agent": self.user_agent,
            },
            params={"limit": limit},
        )
        response.raise_for_status()
        return [post["data"] for post in response.json()["data"]["children"]]

    async def close(self) -> None:
        await self.client.aclose()


# Usage
async def main():
    client = RedditClient(
        client_id="your_id",
        client_secret="your_secret",
        user_agent="YourApp/1.0",
    )
    try:
        posts = await client.get_posts("python", limit=5)
        for post in posts:
            print(f"{post['title']} - {post['score']} upvotes")
    finally:
        await client.close()

TypeScript with fetch

typescript
interface RedditPost {
  title: string;
  score: number;
  url: string;
  selftext: string;
  author: string;
  created_utc: number;
}

class RedditClient {
  private accessToken: string | null = null;

  constructor(
    private clientId: string,
    private clientSecret: string,
    private userAgent: string
  ) {}

  async authenticate(): Promise<void> {
    const auth = Buffer.from(`${this.clientId}:${this.clientSecret}`).toString("base64");

    const response = await fetch("https://www.reddit.com/api/v1/access_token", {
      method: "POST",
      headers: {
        Authorization: `Basic ${auth}`,
        "User-Agent": this.userAgent,
        "Content-Type": "application/x-www-form-urlencoded",
      },
      body: "grant_type=client_credentials",
    });

    const data = await response.json();
    this.accessToken = data.access_token;
  }

  async getPosts(subreddit: string, sort = "hot", limit = 10): Promise<RedditPost[]> {
    if (!this.accessToken) await this.authenticate();

    const response = await fetch(
      `https://oauth.reddit.com/r/${subreddit}/${sort}?limit=${limit}`,
      {
        headers: {
          Authorization: `Bearer ${this.accessToken}`,
          "User-Agent": this.userAgent,
        },
      }
    );

    const data = await response.json();
    return data.data.children.map((child: any) => child.data);
  }
}

OAuth2 Web Flow (User Authorization)

For apps where users log in with their Reddit account:

python
from fastapi import FastAPI, Request
from fastapi.responses import RedirectResponse
import httpx
import secrets

app = FastAPI()
state_store: dict[str, bool] = {}

REDDIT_CLIENT_ID = "your_client_id"
REDDIT_CLIENT_SECRET = "your_client_secret"
REDIRECT_URI = "http://localhost:8000/callback"

@app.get("/login")
async def login():
    state = secrets.token_urlsafe(16)
    state_store[state] = True

    auth_url = (
        f"https://www.reddit.com/api/v1/authorize"
        f"?client_id={REDDIT_CLIENT_ID}"
        f"&response_type=code"
        f"&state={state}"
        f"&redirect_uri={REDIRECT_URI}"
        f"&duration=permanent"
        f"&scope=identity read submit vote"
    )
    return RedirectResponse(auth_url)

@app.get("/callback")
async def callback(code: str, state: str):
    if state not in state_store:
        return {"error": "Invalid state"}
    del state_store[state]

    # Exchange code for token
    async with httpx.AsyncClient() as client:
        response = await client.post(
            "https://www.reddit.com/api/v1/access_token",
            auth=(REDDIT_CLIENT_ID, REDDIT_CLIENT_SECRET),
            data={
                "grant_type": "authorization_code",
                "code": code,
                "redirect_uri": REDIRECT_URI,
            },
            headers={"User-Agent": "YourApp/1.0"},
        )

    tokens = response.json()
    # Store tokens securely, associate with user session
    return {"access_token": tokens["access_token"][:10] + "..."}

Available Scopes

ScopeDescription
identityAccess username and signup date
readAccess posts and comments
submitSubmit links and comments
voteUpvote/downvote content
editEdit posts and comments
historyAccess voting history
subscribeManage subreddit subscriptions
mysubredditsAccess subscribed subreddits
privatemessagesAccess private messages
saveSave/unsave content

Full list: https://www.reddit.com/api/v1/scopes


Project Structure

project/
├── src/
│   ├── reddit/
│   │   ├── __init__.py
│   │   ├── client.py         # Reddit client wrapper
│   │   ├── models.py         # Pydantic models for posts/comments
│   │   └── scraper.py        # Data collection logic
│   └── main.py
├── .env
└── pyproject.toml

Pydantic Models

python
from pydantic import BaseModel
from datetime import datetime

class RedditPost(BaseModel):
    id: str
    title: str
    author: str
    subreddit: str
    score: int
    upvote_ratio: float
    url: str
    selftext: str
    created_utc: datetime
    num_comments: int
    is_self: bool

    @classmethod
    def from_praw(cls, submission) -> "RedditPost":
        return cls(
            id=submission.id,
            title=submission.title,
            author=str(submission.author),
            subreddit=submission.subreddit.display_name,
            score=submission.score,
            upvote_ratio=submission.upvote_ratio,
            url=submission.url,
            selftext=submission.selftext,
            created_utc=datetime.fromtimestamp(submission.created_utc),
            num_comments=submission.num_comments,
            is_self=submission.is_self,
        )

class RedditComment(BaseModel):
    id: str
    author: str
    body: str
    score: int
    created_utc: datetime
    parent_id: str
    is_submitter: bool

Anti-Patterns

  • No User-Agent - Reddit blocks requests without proper User-Agent
  • Ignoring rate limits - Respect 100 QPM, check X-Ratelimit-* headers
  • Storing credentials in code - Use environment variables
  • Not handling MoreComments - Use replace_more() in PRAW
  • Polling instead of streaming - Use .stream for real-time data
  • No error handling - Handle 429 (rate limit), 403 (forbidden), 404 (not found)

Quick Reference

bash
# PRAW installation
pip install praw

# Snoowrap installation
npm install snoowrap

# Test authentication
python -c "import praw; r = praw.Reddit(...); print(r.user.me())"

Endpoints

OperationEndpoint
Auth tokenPOST https://www.reddit.com/api/v1/access_token
API requestshttps://oauth.reddit.com/...
Subreddit postsGET /r/{subreddit}/{sort}
SubmissionGET /comments/{id}
User infoGET /user/{username}/about
Submit postPOST /api/submit
VotePOST /api/vote

Frequently asked questions

What does the Reddit Api AI skill do?

Reddit API with PRAW (Python) and Snoowrap (Node.js)

Why use Reddit Api on TypingMind?

Because you install it once and use it with any model. Reddit Api is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Reddit Api in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alinaqi/maggy/tree/main/skills/reddit-api. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Reddit Api?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Reddit Api?

As many as you like. As long as a model supports skills, you can use Reddit Api with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Reddit Api AI skill free?

Yes. It is published on GitHub by alinaqi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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