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Twitter Monitor

  • 188 installs
  • 431 repo stars
  • Updated July 22, 2026
  • kangarooking/kangarooking-skills

twitter-monitor is an agent skill that fetches X posts into structured exports with optional Feishu sync and scheduled reruns.

About

twitter-monitor is an agent skill that turns X (Twitter) accounts you care about into a repeatable monitoring pipeline for solo builders tracking market narratives, launch chatter, or competitor voices. You supply TWITTER_API_KEY for twitterapi.io and a JSON list of handles or profile URLs; the agent runs twitter_monitor.py and returns rich tweet records including views, likes, reposts, comments, bookmarks, reply flags, and capture timestamps. When you explicitly want Lark operations, the skill defers to feishu-cli with a recommended Bitable schema and deduplication on tweet ID instead of begging for app secrets upfront. Scheduling is offered only after a one-shot fetch works—or when you ask for recurring monitoring—via OpenClaw when you already live there or Codex automations in supported environments. It fits Grow content intelligence and Launch distribution listening, and doubles for Idea competitor surveillance when you paste rival founder accounts into the watch list.

  • One-shot fetch via scripts/twitter_monitor.py with JSON or CSV output
  • Configurable watch list of handles and profile URLs (e.g. sama, elonmusk, OpenAI)
  • Optional Feishu/Lark Bitable append with dedupe on 推文ID and documented field schema
  • Scheduling paths: OpenClaw recurring jobs or Codex automation after a successful manual run
  • TWITTER_API_KEY via twitterapi.io; Feishu only when the user requests Bitable sync

Twitter Monitor by the numbers

  • 188 all-time installs (skills.sh)
  • +4 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #600 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/kangarooking/kangarooking-skills --skill twitter-monitor

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Listed on Skillselion
Installs188
repo stars431
Security audit2 / 3 scanners passed
Last updatedJuly 22, 2026
Repositorykangarooking/kangarooking-skills

What it does

Fetch and normalize tweets from chosen X accounts or profile URLs into JSON or CSV, with optional Feishu Bitable sync and recurring agent scheduling.

Who is it for?

Best when you already use twitterapi.io and want agent-run monitoring with optional Feishu ops tables or OpenClaw/Codex recurrence.

Skip if: Skip if you refuse API keys, need official X enterprise compliance reviews only, or want Feishu setup forced on every run without asking.

When should I use this skill?

User wants to monitor X/Twitter accounts, export tweet JSON or CSV, sync to Feishu/Lark when asked, or schedule recurring fetches after TWITTER_API_KEY is set.

What you get

You get JSON or CSV (and optionally Feishu rows) with deduped tweet IDs and metrics so you can plug signals into content, launch, or competitor workflows on a schedule.

  • JSON or CSV file of tweets with links, IDs, author fields, and engagement counts
  • Optional appended Feishu Bitable rows with dedupe on 推文ID

By the numbers

  • Recommended Feishu Bitable schema lists 13 documented fields including engagement metrics

Files

SKILL.mdMarkdownGitHub ↗

Twitter Monitor

Workflow

Use this skill as an execution workflow, not as a long-running daemon. First complete a one-shot fetch, then offer optional Feishu sync and scheduling only when useful.

1. Ask for X/Twitter account ids when missing. Accept handles such as sama, @sama, profile URLs, or multiple comma-separated ids. 2. Ask the user to provide or configure a twitterapi.io API key when TWITTER_API_KEY is unavailable. Do not write API keys into files committed to a repository. 3. Confirm pagination depth. Default to --pages 1; use a larger number only when the user asks for more history or accepts higher API usage. 4. Run scripts/twitter_monitor.py and generate JSON or CSV output. 5. If the user wants Feishu/Lark Bitable output, follow references/feishu-output.md. 6. After the one-shot command works, ask whether they want recurring execution. If yes, follow references/scheduling.md, including OpenClaw when appropriate.

Quick Start

From this skill directory:

export TWITTER_API_KEY="..."
python scripts/twitter_monitor.py --accounts sama --pages 1 --format json

For multiple accounts:

python scripts/twitter_monitor.py --accounts sama,elonmusk,OpenAI --pages 1 --format csv

For a JSON account list:

python scripts/twitter_monitor.py --accounts-file assets/accounts.example.json --pages 1

Read references/twitterapi-setup.md when the user needs API key setup, account input examples, or command variants.

Output Schema

The script writes one record per tweet with these fields:

  • 推文内容
  • 日期
  • 推文链接
  • 推文ID
  • 作者
  • 作者ID
  • 阅读量
  • 点赞数
  • 转发数
  • 评论数
  • 收藏数
  • 是否回复
  • 抓取时间

Deduplicate by 推文ID before appending to any durable destination.

Feishu

Do not require Feishu configuration for normal fetches. Only enter the Feishu workflow when the user asks to write, append, or sync records to Feishu/Lark Bitable.

Prefer feishu-cli over hard-coded Feishu app credentials. If feishu-cli is missing, ask whether to install and configure it. See references/feishu-output.md for the field mapping and sync rules.

Scheduling

Offer scheduling only after a successful one-shot fetch or when the user explicitly asks for ongoing monitoring.

Prefer OpenClaw when the user wants an agent-managed recurring job or already uses OpenClaw. Otherwise choose Codex automations, cron, or launchd based on the runtime environment. See references/scheduling.md.

Safety

Never commit real API keys, Feishu tokens, output files containing private monitoring data, or local status caches. Keep secrets in environment variables, secret managers, or the user's existing CLI auth.

Related skills

How it compares

Skill-orchestrated fetch and optional Bitable sync—not a hosted social listening SaaS with built-in sentiment models.

FAQ

Who is twitter-monitor for?

It is for developers and small teams using coding agents to watch specific X accounts and export tweet plus engagement data for their own analytics stack.

When should I use twitter-monitor?

Use it in Grow to fuel content decisions, in Idea to track competitor or thought-leader accounts, and in Launch to watch distribution narratives; enable Feishu sync only when you ask to write results to Bitable.

Is twitter-monitor safe to install?

It uses a third-party Twitter API key and may touch Feishu via feishu-cli—review the Security Audits panel on this page and rotate TWITTER_API_KEY if the agent environment is shared.

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