twitter-automation

twitter-automation is a skill for Claude Code from lnvestor/twitr-skills. It costs 251 tokens per session (2,555 once invoked), scanned A, original, MIT.

A tool for building and running automated actions on X (formerly Twitter), including posting, replying, liking, retweeting, following, unfollowing, direct messages, and media posts.

In plain words
What is it for?
Use it to create workflows such as replying to mentions, publishing regular updates, monitoring competitors, or reacting to posts with text or media.
Why use it?
It turns a plain-language goal into a connected workflow that can monitor X and take actions automatically. It also calculates the running cost before paid actions are used.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument; mentions Claude Code; built for openclaw.

Part of the twitr-skills plugin — 6 skills, 1 MCP server shipped together

Good fit Use it to create workflows such as replying to mentions, publishing regular updates, monitoring competitors, or reacting to posts with text or media.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lnvestor/twitr-skills/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 lnvestor/twitr-skills --skill twitter-automation
Clone the repo
git clone --depth 1 https://github.com/lnvestor/twitr-skills

Made for: Claude Code.

Or install twitr-skills, the plugin that ships this one along with the rest of its 6 skills, 1 MCP server.

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/lnvestor/twitr-skills/twitter-automation/github.svg)](https://agentmods.dev/skills/lnvestor/twitr-skills/twitter-automation)
Your own site
<a href="https://agentmods.dev/skills/lnvestor/twitr-skills/twitter-automation"><img src="https://agentmods.dev/badge/skills/lnvestor/twitr-skills/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/lnvestor/twitr-skills/twitter-automation"><img src="https://agentmods.dev/badge/skills/lnvestor/twitr-skills/twitter-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 251 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,555 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 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 $0.00251 $0.02555
Opus 5 $0.00125 $0.01277
Sonnet 5 $0.00050 $0.00511
Haiku 4.5 $0.00025 $0.00255

Measured 12d ago against content hash d970574f7f1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

twitter-automation scanned grade A with 0 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 12d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/twitter-automation/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Twitter/X Automation

Automate X/Twitter via twitr.sh — no developer account, no API keys, no OAuth app review. Every paid call is one POST to https://twitr.sh/api/tools/{tool}; the first call returns HTTP 402 with the exact price, your wallet pays in USDC, the retry runs. Failed calls are never charged.

How to use this skill — you are the automation builder

The user states an outcome ("reply to anyone who mentions my brand", "post my changelog every morning", "alert me when a competitor tweets"). Your job:

  1. Design — compose the automation from the recipe table below.
  2. Price — state the total running cost BEFORE spending: monitor $/day + per-action price (always shown in the 402 before you commit).
  3. Wire it up — connect account (if writing), create the monitor, register the webhook or plan the polling, then run the action loop.
  4. Confirm with the user before creating a monitor or posting as their account. Always.

Recipe table — intent → wiring

User wants Wiring Running cost
Auto-reply to mentions connect account → x_monitor on "query": "@handle" → webhook tweet.mentionx_compose draft → x_write reply ~$0.61/day + ~$0.04/reply
Scheduled posting / "tweet daily" agent-side cron (Claude Code routine, OpenClaw cron) → x_composex_write post ~$0.037/post
Watch an account or topic, get alerted x_monitor (account or keyword) → poll events free, or webhook to your endpoint ~$0.61/day
Repost / mirror media x_read download-media → x_write upload_media → x_write post with media_ids ~$0.05/post
Engagement (like/retweet/follow on a topic) x_monitor keyword → x_write like / retweet / follow ~$0.61/day + ~$0.012/action
DM new engagers x_timeline engagement lists or monitor events → x_write send_dm per item + ~$0.036/DM
One-off post / reply / thread x_composex_write ~$0.037

Automations that publish or engage should stay useful, not spammy — X suspends accounts for aggressive follow/like churn and unsolicited DM blasts. Keep volumes human-scale and tell the user when a design risks their account.

Read the full file on GitHub · 174 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. 12d ago First seen · 174 lines · 251 tokens per session scan A d970574f7f1c

Subscribe to this mod's changes

twitter-automation is a skill published in the GitHub repository lnvestor/twitr-skills (8 stars, last pushed 1mo ago), licensed MIT. It adds 251 tokens to every session and 2,555 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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