twitter-automation

twitter-automation is a skill for Claude Code from J-StaR-Films-Studios/VibeCode-Protocol-Suite. It costs 139 tokens per session (1,089 once invoked), scanned C, original, ISC.

A Twitter/X automation skill for posting, scheduling, liking, retweeting, messaging, and following users.

In plain words
What is it for?
Use it to publish posts with media, manage engagement, send direct messages, and follow accounts.
Why use it?
It removes repetitive social-media actions that would otherwise need to be done manually.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to publish posts with media, manage engagement, send direct messages, and follow accounts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add J-StaR-Films-Studios/VibeCode-Protocol-Suite --skill twitter-automation
Clone the repo
git clone --depth 1 https://github.com/J-StaR-Films-Studios/VibeCode-Protocol-Suite

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for twitter-automation

README.md
[![agentmods](https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation/github.svg)](https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation)
Your own site
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for twitter-automation

Your own site · 80×15
<a href="https://agentmods.dev/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation"><img src="https://agentmods.dev/badge/skills/j-star-films-studios/vibecode-protocol-suite/twitter-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,089 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00139 $0.01089
Opus 5 $0.00069 $0.00544
Sonnet 5 $0.00028 $0.00218
Haiku 4.5 $0.00014 $0.00109

Measured 8d ago against content hash 664c2aaf26e2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

twitter-automation scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -fsSL https://cli.inference.sh | sh && infsh login

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -fsSL https://cli.inference.sh | sh && infsh login
assets/.agent/skills/marketing-growth/twitter-automation/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Twitter/X Automation

Automate Twitter/X via inference.sh CLI.

Quick Start

# Install CLI
curl -fsSL https://cli.inference.sh | sh && infsh login

# Post a tweet
infsh 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

infsh app run x/post-tweet --input '{"text": "Just shipped a new feature! 🚀"}'

Post with Media

infsh 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"
# }

infsh app run x/post-create --input input.json

Like a Tweet

infsh app run x/post-like --input '{"tweet_id": "1234567890"}'

Retweet

infsh app run x/post-retweet --input '{"tweet_id": "1234567890"}'

Send a DM

infsh app run x/dm-send --input '{
  "recipient_id": "user_id_here",
  "text": "Hey! Thanks for the follow."
}'

Follow a User

infsh app run x/user-follow --input '{"username": "elonmusk"}'

Get User Profile

infsh app run x/user-get --input '{"username": "OpenAI"}'

Get Tweet Details

infsh app run x/post-get --input '{"tweet_id": "1234567890"}'

Delete a Tweet

infsh app run x/post-delete --input '{"tweet_id": "1234567890"}'

Workflow: Generate AI Image and Post

# 1. Generate image
infsh app run falai/flux-dev-lora --input '{"prompt": "sunset over mountains"}' > image.json

# 2. Post to Twitter with the image URL
infsh app run x/post-create --input '{
  "text": "AI-generated art of a sunset 🌅",
  "media_url": "<image-url-from-step-1>"
}'

Read the full file on GitHub · 158 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 158 lines · 139 tokens per session scan C 664c2aaf26e2

Subscribe to this mod's changes

twitter-automation is a skill published in the GitHub repository J-StaR-Films-Studios/VibeCode-Protocol-Suite (24 stars, last pushed today), licensed ISC. It adds 139 tokens to every session and 1,089 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

happiness-skill

A Chinese-language guide to happiness based on reducing unmet wants, focusing on the present, and treating happiness as a trainable skill.

kangarooking/cangjie-skill · 136 tokens

setup-matt-pocock-skills

A setup skill that configures engineering skills for a repository, including its issue tracker, labels, and documentation layout. A repository is the project folder managed by version control.

devcxl/mattpocock-skills-zh · 43 tokens

frontend-design

A design guide for building polished web interfaces such as pages, dashboards, forms, navigation, and reusable UI components. It covers HTML, CSS, JavaScript, and common frontend frameworks.

AnastasiyaW/codex-claude-code-config · 264 tokens

alterlab-cobrapy

Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting growth or knockout phenotypes, or running systems-biology and…

AlterLab-IEU/AlterLab-Academic-Skills · 91 tokens

alterlab-depmap

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use when identifying cancer-specific genetic vulnerabilities, finding synthetic lethal interactions, checking whether a gene is essential in given cell lines, or…

AlterLab-IEU/AlterLab-Academic-Skills · 77 tokens

alterlab-qutip

Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time…

AlterLab-IEU/AlterLab-Academic-Skills · 134 tokens