Twitter Automation Agent Skill
Automate Twitter/X with posting, engagement, and user management via inference.sh CLI. Apps: x/post-tweet, x/post-create (with media), x/post-like, x/post-retweet, x/dm-send, x/user-follow. Capabilities: post tweets, schedule content, like posts, retweet, send DMs, follow users, get profiles. Use for: social media automation, content scheduling, engagement bots, audience growth, X API. Triggers: twitter api, x api, tweet automation, post to twitter, twitter bot, social media automation, x automation, tweet scheduler, twitter integration, post tweet, twitter post, x post, send tweet
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/aiskillstore/marketplace --skill twitter-automationWhat comes with it
55 832 bytes besides the instructionWhat it tells the agent to use
found in the instruction textThe instruction itself
17 sections, as written by the author> Install the belt CLI skill: npx skills add belt-sh/cli
Twitter/X Automation
Automate Twitter/X via inference.sh CLI.
Quick Start
> Requires inference.sh CLI (belt). Install instructions
belt login
# Post a tweet
belt app run x/post-tweet --input '{"text": "Hello from inference.sh!"}'
Available Apps
| App | App ID | Description |
|-----|--------|-------------|
| Post Tweet | x/post-tweet | Post text tweets |
| Create Post | x/post-create | Post with media |
| Like Post | x/post-like | Like a tweet |
| Retweet | x/post-retweet | Retweet a post |
| Delete Post | x/post-delete | Delete a tweet |
| Get Post | x/post-get | Get tweet by ID |
| Send DM | x/dm-send | Send direct message |
| Follow User | x/user-follow | Follow a user |
| Get User | x/user-get | Get user profile |
Examples
Post a Tweet
belt app run x/post-tweet --input '{"text": "Just shipped a new feature! 🚀"}'
Post with Media
belt app sample x/post-create --save input.json
# Edit input.json:
# {
# "text": "Check out this AI-generated image!",
# "media_url": "https://your-image-url.jpg"
# }
belt app run x/post-create --input input.json
Like a Tweet
belt app run x/post-like --input '{"tweet_id": "1234567890"}'
Retweet
belt app run x/post-retweet --input '{"tweet_id": "1234567890"}'
Send a DM
belt app run x/dm-send --input '{
"recipient_id": "user_id_here",
"text": "Hey! Thanks for the follow."
}'
Follow a User
belt app run x/user-follow --input '{"username": "elonmusk"}'
Get User Profile
belt app run x/user-get --input '{"username": "OpenAI"}'
Get Tweet Details
belt app run x/post-get --input '{"tweet_id": "1234567890"}'
Delete a Tweet
belt app run x/post-delete --input '{"tweet_id": "1234567890"}'
Workflow: Generate AI Image and Post
# 1. Generate image
belt app run falai/flux-dev-lora --input '{"prompt": "sunset over mountains"}' > image.json
# 2. Post to Twitter with the image URL
belt app run x/post-create --input '{
"text": "AI-generated art of a sunset 🌅",
"media_url": "<image-url-from-step-1>"
}'
Workflow: Generate and Post Video
# 1. Generate video
belt app run google/veo-3-1-fast --input '{"prompt": "waves on a beach"}' > video.json
# 2. Post to Twitter
belt app run x/post-create --input '{
"text": "AI-generated video 🎬",
"media_url": "<video-url-from-step-1>"
}'
Related Skills
# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli
# Image generation (create images to post)
npx skills add inference-sh/skills@ai-image-generation
# Video generation (create videos to post)
npx skills add inference-sh/skills@ai-video-generation
# AI avatars (create presenter videos)
npx skills add inference-sh/skills@ai-avatar-video
Browse all apps: belt app store
Documentation
- X.com Integration - Setting up Twitter/X integration
- X.com Integration Example - Complete Twitter workflow
- Apps Overview - Understanding the app ecosystem
Other skills for the same job
different authors, same section of the catalogue
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
| Automate Twitter/X with posting, engagement, and user management via inference.sh CLI. social media automation, x automation, tweet scheduler, twitter integration, post tweet, twitter post, x post, send tweet
| Query the Sequence Read Archive (SRA), retrieve scientific publications, and analyze genomics metadata using the SRAgent toolkit. Supports accession conversion (GSE→SRX→SRR), BigQuery metadata queries, manuscript downloads from multiple sources, and scRNA-seq technology identification. Use when working with SRA/GEO datasets, finding publications, or analyzing single-cell sequencing experiments.
Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.
> Analyzes unit economics by product or service using PayPal merchant insights and QuickBooks cost data, benchmarks against inflation and cost changes, and shows pricing-scenario data (e.g. "a 5% increase historically correlates with ~3% volume drop"). Surfaces analysis only — does not recommend a price. Use when the user asks about raising prices, pricing, margin analysis, what to charge, whether costs are eating into profit, or how a price change might affect their business. Trigger even if the user doesn't say "margin" explicitly — phrases like "am I making enough?", "should I charge more?", or "my costs are going up" all call for this skill.
Define a dataset's metadata profile — infer a Frictionless Table Schema from its data, add Data Package metadata (license, sources, keywords), and write it into datasets.json so the showcase renders a typed field table. Extend or customize via the L0-L3 profile ladder. Use when a registered dataset needs field types, constraints, or catalog metadata before publishing.
How to use it
Take aiskillstore/twitter-automation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.