Track X Accounts with the twitter-monitor Skill

Where this fits

A developer is building an AI agent that must watch a set of X/Twitter accounts for new posts, capture engagement metrics, and append them to a company Feishu Bitable. Doing this manually or with ad-hoc scripts quickly becomes brittle. The twitter-monitor skill packages the fetch, structured export, optional Feishu sync, and scheduling guidance into one reproducible workflow that agents can run on demand.

Why agents benefit

• Fetches normalized data: Converts raw X/Twitter API responses into structured JSON/CSV records, so downstream tools can parse tweets without bespoke logic.
• Handles input ambiguity: Accepts handles, @mentions, profile URLs, or comma-separated account IDs, making it easy for an agent to interpret user intent.
• Offers optional sync: Uses feishu-cli to append records to a Feishu/Lark Bitable, enabling automated collection pipelines without extra glue code.
• Supports scheduled execution: Provides guidance for recurring runs via OpenClaw, Codex automations, cron, or launchd, so agents can maintain a live tracker.
• Respects API usage: Defaults to one page of results and only increases pagination when explicitly requested, preventing accidental cost spikes.

Practical scenarios

Researching blogger output for a weekly newsletter

An agent checks a list of five AI researchers’ X accounts every Sunday, fetches their latest posts, and writes a Markdown digest. The skill outputs clean CSV, making the agent’s summarization step straightforward.

Building a competitive intelligence tracker

A product team wants to monitor competitor announcements. With twitter-monitor, the agent fetches new posts hourly, appends them to a Feishu Bitable, and alerts the team when specific keywords appear.

Archiving tweet metrics for analysis

A data analyst needs historical engagement numbers for influencer campaign evaluation. The agent fetches multiple pages for a set of accounts, exports JSON, and schedules the same fetch daily to accumulate a time series.

Add it to your agent workflow

Install the skill directly with npx:

npx skills add kangarooking/kangarooking-skills --skill twitter-monitor

After installation, ask the agent to fetch recent posts from an account and export them:

Monitor @sama from X, fetch the latest 5 tweets, and save them as CSV.

The agent will prompt for a twitterapi.io key if TWITTER_API_KEY is not already set, confirm pagination depth, and run scripts/twitter_monitor.py to produce the records. You can then request a Feishu Bitable sync if that integration is configured.

Compare before adopting

Before adding twitter-monitor to your stack, compare it against alternatives by checking:

• Quality signals: Is the skill actively maintained? Look at the GitHub repo’s recent commits, open issues, and whether the README reflects current API changes.
• Maintenance freshness: X/Twitter APIs change often; a skill last updated a year ago may break.
• Alternatives: Other X-monitoring skills may offer different export formats or native Feishu integration. Evaluate whether the script’s dependencies match your runtime environment.
• Workflow fit: The skill is intentionally workflow-based, not a daemon—confirm that matches how your agent schedules tasks.

Why it is worth tracking

With 568 stars and a focused scope, twitter-monitor shows community interest in turning X/Twitter monitoring into a repeatable agent capability. Its combination of structured output, optional Feishu sync, and scheduling guidance fills a real gap. Keep an eye on the repository for updates around API limits and new export options, and revisit the skill when your tracking needs grow. For a summary and community context, see the OpenAgentSkill listing at https://www.openagentskill.com/skills/kangarooking-twitter-monitor.