Guide · Agent skill
How to use the Social Media Intelligence agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The social-media-intelligence skill is a reference guide that teaches an AI agent how financial discussion works on Twitter/X, Telegram, Discord and Reddit. It explains which kinds of accounts and channels tend to carry useful signals, includes example Python code for collecting posts, and gives a standard JSON layout for storing them. After this guide you will know how to install the skill, ask for it in plain language, and what it needs before it can help.
Social Media IntelligenceHKUDS/Vibe-Trading · MIT Download the skill Quick start
- 1Download the ZIP. Get the skill ZIP from its page on this directory.
- 2Install the skill. Unzip it into ~/.claude/skills/ for personal use or into .claude/skills/ in a project, or upload it under Settings → Capabilities → Skills in the Claude apps.
- 3Set up credentials. Create the keys you need, such as a Twitter/X bearer token or Telegram API_ID and API_HASH, and store them in TWITTER_BEARER_TOKEN, TELEGRAM_API_ID and TELEGRAM_API_HASH.
- 4Install the Python libraries. Install tweepy, telethon, and optionally ntscraper or discord.py, depending on which platforms you plan to use.
- 5Ask for what you need. Describe the platform, asset or channel and the output you want in plain language, such as a collector plus the JSON layout.
- 6Review before running. Read any code the agent produces, check the platform's terms, and confirm what personal data you will store before you run it.
What does the skill make the agent do?
The skill is a single file, SKILL.md. When the agent loads it, it gets background on four platforms: which account types on Twitter/X, channel types on Telegram, community types on Discord and subreddits on Reddit tend to carry financial signal, and which carry mostly noise. It also gives the agent code samples for pulling posts and a JSON layout for storing them.
The skill is guidance and code, not a running program. It does not execute anything on its own. The agent can help you adapt the samples into a research pipeline for sentiment-driven trading research.
- Explains the roles of Twitter/X accounts, from sell-side analysts and fund managers to retail noise, and how much signal each usually gives.
- Describes Telegram channel types such as signal, research push, macro flash and whale alert channels.
- Lists Discord community types and Reddit subreddits such as r/wallstreetbets, r/investing and r/options.
- Provides Python examples for collecting tweets and Telegram channel messages, plus a Discord example.
- Provides JSON schemas for storing Twitter and Telegram posts, and suggests how often to collect each source.
How do you install the skill?
You can install the skill for yourself or for a single project. Download the ZIP from the skill's page on this directory, then choose one of the options below.
If you use Claude Code, unzip the skill into ~/.claude/skills/ for personal use, or into .claude/skills/ inside a project folder if you want it limited to that project. In the Claude apps, you can instead upload the skill under Settings → Capabilities → Skills.
- Personal install: unzip into ~/.claude/skills/.
- Project install: unzip into .claude/skills/ in your project.
- Claude apps: go to Settings → Capabilities → Skills and upload the ZIP.
How do you trigger the skill with natural requests?
You do not need a special command. Describe what you want in plain language that involves financial discussion on one of the four platforms. The skill's description covers financial signal extraction from these platforms for sentiment-driven trading strategies, so requests that match that topic are the ones it is meant to handle.
Name the platform and the asset or channel where you can. The more specific the request, the more useful the code and schema the agent produces.
- Show me how to collect recent $AAPL cashtag tweets with tweepy and store them in the Twitter JSON layout.
- Which kinds of Telegram channels are useful for crypto sentiment, and which are noisy?
- Write a collector for messages from a Telegram channel using telethon and the API_ID and API_HASH in my environment variables.
- Which subreddits are most relevant for retail sentiment on options?
- How often should I poll a whale alert channel versus a research channel?
What do you need before you start?
The skill's examples use several Python libraries and credentials. Set up only the parts you need. The official Twitter/X route needs a paid API tier and a bearer token. The Telegram route needs API credentials from Telegram. Discord needs a bot.
The skill lists these environment variables: TWITTER_BEARER_TOKEN, TELEGRAM_API_ID and TELEGRAM_API_HASH. The Discord example uses a Bot Token and needs the bot to be invited to the server.
- Python.
- tweepy for the Twitter/X API v2. The skill notes the paid basic tier starts at about $100/month and requires a bearer token.
- ntscraper for an unofficial, optional Nitter-based Twitter/X scraper.
- telethon, which requires Telegram API_ID and API_HASH credentials.
- discord.py, which uses the official Bot API and requires a Bot Token.
- Environment variables: TWITTER_BEARER_TOKEN, TELEGRAM_API_ID, TELEGRAM_API_HASH.
pip install telethon
pip install ntscraper
pip install discord.pyWhat are the safety notes for scripts and network use?
The skill does not run scripts. It does use the network, because the example code it contains calls external platforms once you run it yourself. Check the terms of each platform before you collect data.
The unofficial Nitter option is fragile and may violate platform rules, so the skill recommends the official API for production work. The schemas also store usernames and follower counts, which raises privacy questions if you collect data about individual people.
- Use the official API routes where compliance matters.
- Do not rely on ntscraper for production; it is unofficial and fragile.
- Store only the fields your research needs, and think about privacy before keeping usernames or follower counts.
- Social sentiment can be manipulated, so do not treat a spike in posts as proof of a price move.
What tips help you get useful results?
Match collection frequency to the source. The skill suggests polling Twitter/X every 5 minutes during earnings season or major events and hourly for routine monitoring. Telegram signal channels suit a 30-minute cadence, and research channels suit a daily batch.
Treat signal channels as a sentiment thermometer, not as a source to copy-trade. Many fields in the sample schemas, such as sentiment_score, are null by default. Your own scoring method has to fill them in.
- Filter out retweets and non-English posts with the query the Twitter example uses.
- Use official project channels for updates, but expect to filter promotion.
- Keep the raw posts alongside any scores you compute so you can re-check them later.
- Ask the agent to explain why it chose a source type before you build around it.
What people use it for
- Building a collector that pulls cashtag discussion for a stock or crypto asset from Twitter/X into a consistent JSON layout.
- Comparing which Telegram channel types carry useful information and which are mostly noise before choosing sources for a study.
- Planning a polling schedule that matches how fast each platform moves, from real-time alerts to daily research batches.
- Choosing Reddit subreddits to watch for retail sentiment on options or long-horizon investing.
Frequently asked questions
Is the Social Media Intelligence skill free?
The skill's listing is under the MIT licence. The tools it uses have their own costs: the skill notes that the official Twitter/X API v2 basic tier starts at about $100 a month, while ntscraper is an optional unofficial scraper. The file does not state Telegram or Discord pricing, so check those platforms directly.
Do I need a Twitter/X API key to use this skill?
For the official route, yes. The tweepy example needs a bearer token, which the skill expects in the TWITTER_BEARER_TOKEN environment variable. ntscraper, the unofficial option, is listed as optional and does not use that token.
Does this skill give me trading signals?
No. The skill is educational and does not provide tested strategies or returns. It helps you understand which sources carry useful information and how to store posts for your own research.
How do I install an agent skill in Claude?
Download the skill ZIP, then unzip it into ~/.claude/skills/ for personal use or into .claude/skills/ in a project. In the Claude apps, you can upload the ZIP under Settings → Capabilities → Skills instead.
Is it legal to scrape Twitter with Nitter?
The skill warns that the unofficial Nitter option is fragile and may violate platform rules. Read the platform's terms before you collect anything, and prefer the official API for work you plan to rely on.
How does this compare with a hosted social sentiment tool?
This skill is a guide plus code samples that you run yourself, with no hosted service or data feed. If you want ready-made dashboards or signals, a hosted product is a different choice; this skill suits people who want to build and understand their own collection pipeline.
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Our verdict
Use this skill if you are a quant researcher, developer or trader who wants an agent to help design social-sentiment research and collection code. Pick something else if you want ready-made signals or guaranteed returns, or if you plan to scrape platforms against their terms of service.
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